From 526c96980bb9fa08763a3601da2fd99019f72fb6 Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Fri, 27 Mar 2026 19:39:37 +0000 Subject: [PATCH 01/24] add Docker support: skip venv, install only missing deps --- studio/install_python_stack.py | 345 ++++++++++++++------------------- studio/setup.sh | 41 +++- unsloth_cli/commands/studio.py | 96 ++++----- 3 files changed, 229 insertions(+), 253 deletions(-) diff --git a/studio/install_python_stack.py b/studio/install_python_stack.py index 2b9fd084d4..1ef626ce39 100644 --- a/studio/install_python_stack.py +++ b/studio/install_python_stack.py @@ -841,216 +841,153 @@ def install_python_stack() -> int: base_total += 3 _TOTAL = (base_total - 1) if skip_base else base_total - # 1. Try to use uv for faster installs (must happen before pip upgrade - # because uv venvs don't include pip by default) - USE_UV = _bootstrap_uv() + # # 1. Try to use uv for faster installs (must happen before pip upgrade + # # because uv venvs don't include pip by default) + # USE_UV = _bootstrap_uv() - # 2. Ensure pip is available (uv venvs created by install.sh don't include pip) - _progress("pip bootstrap") - if USE_UV: - run( - "Bootstrapping pip via uv", - [ - "uv", - "pip", - "install", - "--python", - sys.executable, - "pip", - ], - ) - else: - # pip may not exist yet (uv-created venvs omit it). Try ensurepip - # first, then upgrade. Only fall back to a direct upgrade when pip - # is already present. - _has_pip = ( - subprocess.run( - [sys.executable, "-m", "pip", "--version"], - stdout = subprocess.DEVNULL, - stderr = subprocess.DEVNULL, - ).returncode - == 0 - ) + # # 2. Ensure pip is available (uv venvs created by install.sh don't include pip) + # _progress("pip bootstrap") + # if USE_UV: + # run( + # "Bootstrapping pip via uv", + # [ + # "uv", + # "pip", + # "install", + # "--python", + # sys.executable, + # "pip", + # ], + # ) + # else: + # # pip may not exist yet (uv-created venvs omit it). Try ensurepip + # # first, then upgrade. Only fall back to a direct upgrade when pip + # # is already present. + # _has_pip = ( + # subprocess.run( + # [sys.executable, "-m", "pip", "--version"], + # stdout = subprocess.DEVNULL, + # stderr = subprocess.DEVNULL, + # ).returncode + # == 0 + # ) + # + # if not _has_pip: + # run( + # "Bootstrapping pip via ensurepip", + # [sys.executable, "-m", "ensurepip", "--upgrade"], + # ) + # else: + # run( + # "Upgrading pip", + # [sys.executable, "-m", "pip", "install", "--upgrade", "pip"], + # ) - if not _has_pip: - run( - "Bootstrapping pip via ensurepip", - [sys.executable, "-m", "ensurepip", "--upgrade"], - ) - else: - run( - "Upgrading pip", - [sys.executable, "-m", "pip", "install", "--upgrade", "pip"], - ) + # # 3. Core packages: unsloth-zoo + unsloth (or custom package name) + # if skip_base: + # print(_green(f"✅ {package_name} already installed — skipping base packages")) + # elif NO_TORCH: + # # No-torch update path: install unsloth + unsloth-zoo with --no-deps + # # (current PyPI metadata still declares torch as a hard dep), then + # # runtime deps with --no-deps (avoids transitive torch). + # _progress("base packages (no torch)") + # pip_install( + # f"Updating {package_name} + unsloth-zoo (no-torch mode)", + # "--no-cache-dir", + # "--no-deps", + # "--upgrade-package", + # package_name, + # "--upgrade-package", + # "unsloth-zoo", + # package_name, + # "unsloth-zoo", + # ) + # pip_install( + # "Installing no-torch runtime deps", + # "--no-cache-dir", + # "--no-deps", + # req = REQ_ROOT / "no-torch-runtime.txt", + # ) + # if local_repo: + # pip_install( + # "Overlaying local repo (editable)", + # "--no-cache-dir", + # "--no-deps", + # "-e", + # local_repo, + # constrain = False, + # ) + # elif local_repo: + # _progress("base packages") + # pip_install( + # "Updating base packages", + # "--no-cache-dir", + # "--upgrade-package", + # "unsloth", + # "--upgrade-package", + # "unsloth-zoo", + # req = REQ_ROOT / "base.txt", + # ) + # pip_install( + # "Overlaying local repo (editable)", + # "--no-cache-dir", + # "--no-deps", + # "-e", + # local_repo, + # constrain = False, + # ) + # elif package_name != "unsloth": + # _progress("base packages") + # pip_install( + # f"Installing {package_name}", + # "--no-cache-dir", + # package_name, + # ) + # else: + # _progress("base packages") + # pip_install( + # "Updating base packages", + # "--no-cache-dir", + # "--upgrade-package", + # "unsloth", + # "--upgrade-package", + # "unsloth-zoo", + # req = REQ_ROOT / "base.txt", + # ) - # 3. Core packages: unsloth-zoo + unsloth (or custom package name) - if skip_base: - pass - elif NO_TORCH: - # No-torch update path: install unsloth + unsloth-zoo with --no-deps - # (current PyPI metadata still declares torch as a hard dep), then - # runtime deps with --no-deps (avoids transitive torch). - _progress("base packages (no torch)") - pip_install( - f"Updating {package_name} + unsloth-zoo (no-torch mode)", - "--no-cache-dir", - "--no-deps", - "--upgrade-package", - package_name, - "--upgrade-package", - "unsloth-zoo", - package_name, - "unsloth-zoo", - ) - pip_install( - "Installing no-torch runtime deps", - "--no-cache-dir", - "--no-deps", - req = REQ_ROOT / "no-torch-runtime.txt", - ) - if local_repo: - pip_install( - "Overlaying local repo (editable)", - "--no-cache-dir", - "--no-deps", - "-e", - local_repo, - constrain = False, - ) - elif local_repo: - # Local dev install: update deps from base.txt, then overlay the - # local checkout as an editable install (--no-deps so torch is - # never re-resolved). - _progress("base packages") - pip_install( - "Updating base packages", - "--no-cache-dir", - "--upgrade-package", - "unsloth", - "--upgrade-package", - "unsloth-zoo", - req = REQ_ROOT / "base.txt", - ) - pip_install( - "Overlaying local repo (editable)", - "--no-cache-dir", - "--no-deps", - "-e", - local_repo, - constrain = False, - ) - elif package_name != "unsloth": - # Custom package name (e.g. roland-sloth for testing) — install directly - _progress("base packages") - pip_install( - f"Installing {package_name}", - "--no-cache-dir", - package_name, - ) - else: - # Update path: upgrade only unsloth + unsloth-zoo while preserving - # existing torch/CUDA installations. Torch is pre-installed by - # install.sh / setup.ps1; --upgrade-package targets only base pkgs. - _progress("base packages") - pip_install( - "Updating base packages", - "--no-cache-dir", - "--upgrade-package", - "unsloth", - "--upgrade-package", - "unsloth-zoo", - req = REQ_ROOT / "base.txt", - ) + # pip_install( + # "Installing additional unsloth dependencies", + # "--no-cache-dir", + # req = REQ_ROOT / "extras.txt", + # ) - # 2b. AMD ROCm: reinstall torch with HIP wheels if the host has ROCm but the - # venv received CPU-only torch (common when pip resolves torch from PyPI). - # Must come immediately after base packages so torch is present for inspection. - if not IS_WINDOWS and not IS_MACOS and not NO_TORCH: - _progress("ROCm torch check") - _ensure_rocm_torch() + # pip_install( + # "Installing extras (no-deps)", + # "--no-deps", + # "--no-cache-dir", + # req = REQ_ROOT / "extras-no-deps.txt", + # ) - # Windows + AMD GPU: PyTorch does not publish ROCm wheels for Windows. - # Detect and warn so users know manual steps are needed for GPU training. - if IS_WINDOWS and not NO_TORCH and not _has_usable_nvidia_gpu(): - # Validate actual AMD GPU presence (not just tool existence) - import re as _re_win + # # 4. Overrides (torchao, transformers) -- force-reinstall + # _progress("dependency overrides") + # pip_install( + # "Installing dependency overrides", + # "--force-reinstall", + # "--no-cache-dir", + # req = REQ_ROOT / "overrides.txt", + # ) - def _win_amd_smi_has_gpu(stdout: str) -> bool: - return bool(_re_win.search(r"(?im)^gpu\s*[:\[]\s*\d", stdout)) - - _win_amd_gpu = False - for _wcmd, _check_fn in ( - (["hipinfo"], lambda out: "gcnarchname" in out.lower()), - (["amd-smi", "list"], _win_amd_smi_has_gpu), - ): - _wexe = shutil.which(_wcmd[0]) - if not _wexe: - continue - try: - _wr = subprocess.run( - [_wexe, *_wcmd[1:]], - stdout = subprocess.PIPE, - stderr = subprocess.DEVNULL, - text = True, - timeout = 10, - ) - except Exception: - continue - if _wr.returncode == 0 and _check_fn(_wr.stdout): - _win_amd_gpu = True - break - if _win_amd_gpu: - _safe_print( - _dim(" Note:"), - "AMD GPU detected on Windows. ROCm-enabled PyTorch must be", - ) - _safe_print( - " " * 8, - "installed manually. See: https://docs.unsloth.ai/get-started/install-and-update/amd", - ) - - # 3. Extra dependencies - _progress("unsloth extras") - pip_install( - "Installing additional unsloth dependencies", - "--no-cache-dir", - req = REQ_ROOT / "extras.txt", - ) - - # 3b. Extra dependencies (no-deps) -- audio model support etc. - _progress("extra codecs") - pip_install( - "Installing extras (no-deps)", - "--no-deps", - "--no-cache-dir", - req = REQ_ROOT / "extras-no-deps.txt", - ) - - # 4. Overrides (torchao, transformers) -- force-reinstall - # Skip entirely when torch is unavailable (e.g. Intel Mac GGUF-only mode) - # because overrides.txt contains torchao which requires torch. - if NO_TORCH: - _progress("dependency overrides (skipped, no torch)") - else: - _progress("dependency overrides") - pip_install( - "Installing dependency overrides", - "--force-reinstall", - "--no-cache-dir", - req = REQ_ROOT / "overrides.txt", - ) - - # 5. Triton kernels (no-deps, from source) - # Skip on Windows (no support) and macOS (no support). - if not IS_WINDOWS and not IS_MACOS: - _progress("triton kernels") - pip_install( - "Installing triton kernels", - "--no-deps", - "--no-cache-dir", - req = REQ_ROOT / "triton-kernels.txt", - constrain = False, - ) + # # 5. Triton kernels (no-deps, from source) + # # Skip on Windows (no support) and macOS (no support). + # if not IS_WINDOWS and not IS_MACOS: + # _progress("triton kernels") + # pip_install( + # "Installing triton kernels", + # "--no-deps", + # "--no-cache-dir", + # req = REQ_ROOT / "triton-kernels.txt", + # constrain = False, + # ) if not IS_WINDOWS and not IS_MACOS and not NO_TORCH: _progress("flash-attn") diff --git a/studio/setup.sh b/studio/setup.sh index c2044b5141..d2bd9485ba 100755 --- a/studio/setup.sh +++ b/studio/setup.sh @@ -392,7 +392,7 @@ if [ -d "$SCRIPT_DIR/backend/core/data_recipe/oxc-validator" ] && command -v npm fi # ── Python venv + deps ── -STUDIO_HOME="$HOME/.unsloth/studio" +STUDIO_HOME="${UNSLOTH_STUDIO_HOME:-$HOME/.unsloth/studio}" VENV_DIR="$STUDIO_HOME/unsloth_studio" VENV_T5_530_DIR="$STUDIO_HOME/.venv_t5_530" VENV_T5_550_DIR="$STUDIO_HOME/.venv_t5_550" @@ -405,7 +405,12 @@ VENV_T5_550_DIR="$STUDIO_HOME/.venv_t5_550" # Note: do NOT delete $STUDIO_HOME/.venv here — install.sh handles migration _COLAB_NO_VENV=false -if [ ! -x "$VENV_DIR/bin/python" ]; then +_DOCKER_NO_VENV=false +if [ -n "$UNSLOTH_DOCKER" ]; then + # Docker: packages already in /opt/conda — skip venv entirely. + # Only pre-install .venv_t5 for transformers 5.x switching (handled below). + _DOCKER_NO_VENV=true +elif [ ! -x "$VENV_DIR/bin/python" ]; then if [ "$IS_COLAB" = true ]; then # On Colab there is no Studio venv -- install backend deps into system Python. # Strip all version constraints so pip keeps Colab's pre-installed @@ -470,6 +475,38 @@ if [ "$_COLAB_NO_VENV" = true ]; then substep "continuing to llama.cpp install for GGUF inference support" fi +# In Docker, packages are pre-installed in /opt/conda — only install missing +# studio/data-designer deps and pre-install .venv_t5 for transformers 5.x. +if [ "$_DOCKER_NO_VENV" = true ]; then + echo " Docker detected — skipping venv activation." + + # Install branch's unsloth/unsloth_cli/studio into /opt/conda + # (overwrites PyPI version with Docker-aware code) + echo " Installing local unsloth from branch..." + pip install --force-reinstall --no-deps "$REPO_ROOT" + + # Install only missing deps (studio, data-designer, plugin, metadata patch). + # Heavy packages (torch, unsloth, vllm, etc.) are already in /opt/conda. + # install_python_stack.py has steps 1-5 commented out for this branch. + python "$SCRIPT_DIR/install_python_stack.py" + + # Pre-install transformers 5.x into .venv_t5 + echo "" + echo " Pre-installing transformers 5.x for newer model support..." + mkdir -p "$VENV_T5_DIR" + pip install --target "$VENV_T5_DIR" --no-deps "transformers==5.3.0" 2>/dev/null + pip install --target "$VENV_T5_DIR" --no-deps "huggingface_hub==1.7.1" 2>/dev/null + pip install --target "$VENV_T5_DIR" --no-deps "hf_xet==1.4.2" 2>/dev/null + pip install --target "$VENV_T5_DIR" "tiktoken" 2>/dev/null + echo "✅ Transformers 5.x pre-installed to $VENV_T5_DIR/" + + echo "" + echo "╔══════════════════════════════════════╗" + echo "║ Docker Studio Setup Complete! ║" + echo "╚══════════════════════════════════════╝" + exit 0 +fi + # ── Check if Python deps need updating ── # Compare installed package version against PyPI latest. # Skip all Python dependency work if versions match (fast update path). diff --git a/unsloth_cli/commands/studio.py b/unsloth_cli/commands/studio.py index a3c0840be1..ddc6216d08 100644 --- a/unsloth_cli/commands/studio.py +++ b/unsloth_cli/commands/studio.py @@ -158,56 +158,58 @@ def studio_default( if ctx.invoked_subcommand is not None: return - # Always use the studio venv if it exists and we're not already in it - studio_venv_dir = STUDIO_HOME / "unsloth_studio" - in_studio_venv = sys.prefix.startswith(str(studio_venv_dir)) + # In Docker, packages live in /opt/conda — skip venv re-exec entirely. + if not os.environ.get("UNSLOTH_DOCKER"): + # Always use the studio venv if it exists and we're not already in it + studio_venv_dir = STUDIO_HOME / "unsloth_studio" + in_studio_venv = sys.prefix.startswith(str(studio_venv_dir)) - if not in_studio_venv: - studio_python = _studio_venv_python() - run_py = _find_run_py() - if studio_python and run_py: - if not silent: - typer.echo("Launching Unsloth Studio... Please wait...") - args = [ - str(studio_python), - str(run_py), - "--host", - host, - "--port", - str(port), - ] - if frontend: - args.extend(["--frontend", str(frontend)]) - if silent: - args.append("--silent") - # On Windows, os.execvp() spawns a child but the parent lingers, - # so Ctrl+C only kills the parent leaving the child orphaned. - # Use subprocess.run() on Windows so the parent waits for the child. - if sys.platform == "win32": - import subprocess as _sp + if not in_studio_venv: + studio_python = _studio_venv_python() + run_py = _find_run_py() + if studio_python and run_py: + if not silent: + typer.echo("Launching Unsloth Studio... Please wait...") + args = [ + str(studio_python), + str(run_py), + "--host", + host, + "--port", + str(port), + ] + if frontend: + args.extend(["--frontend", str(frontend)]) + if silent: + args.append("--silent") + # On Windows, os.execvp() spawns a child but the parent lingers, + # so Ctrl+C only kills the parent leaving the child orphaned. + # Use subprocess.run() on Windows so the parent waits for the child. + if sys.platform == "win32": + import subprocess as _sp - proc = _sp.Popen(args) - try: - rc = proc.wait() - except KeyboardInterrupt: - # Child has its own signal handler — let it finish - rc = proc.wait() - if rc != 0: - typer.echo( - f"\nError: Studio server exited unexpectedly (code {rc}).", - err = True, - ) - typer.echo( - "Check the error above. If a package is missing, " - "re-run: unsloth studio setup", - err = True, - ) - raise typer.Exit(rc) + proc = _sp.Popen(args) + try: + rc = proc.wait() + except KeyboardInterrupt: + # Child has its own signal handler — let it finish + rc = proc.wait() + if rc != 0: + typer.echo( + f"\nError: Studio server exited unexpectedly (code {rc}).", + err = True, + ) + typer.echo( + "Check the error above. If a package is missing, " + "re-run: unsloth studio setup", + err = True, + ) + raise typer.Exit(rc) + else: + os.execvp(str(studio_python), args) else: - os.execvp(str(studio_python), args) - else: - typer.echo("Studio not set up. Run install.sh first.") - raise typer.Exit(1) + typer.echo("Studio not set up. Run install.sh first.") + raise typer.Exit(1) from studio.backend.run import run_server From 9c2b6a2560a0b11d3b6b78174a5deb46681f5302 Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Thu, 2 Apr 2026 23:24:47 +0000 Subject: [PATCH 02/24] fix: patch PEFT for Gemma4ClippableLinear in loader checkpoint path The same Gemma4ClippableLinear monkey-patch that exists in vision.py for training is needed in loader.py for loading existing checkpoints (used by export and inference). Gemma4ClippableLinear wraps nn.Linear but does not subclass it, so PEFT's LoRA injection fails with "Target module not supported". The patch redirects PEFT to target the inner .linear child instead. Applied only to the vision model PeftModel.from_pretrained path. Temporary fix until PEFT adds native support (peft#3129). --- unsloth/models/loader.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/unsloth/models/loader.py b/unsloth/models/loader.py index cd12544ae9..362d74559b 100644 --- a/unsloth/models/loader.py +++ b/unsloth/models/loader.py @@ -1562,7 +1562,10 @@ class FastModel(FastBaseModel): if _clippable_linear_cls is not None: from peft.tuners.lora.model import LoraModel as _LoraModel +<<<<<<< HEAD +======= +>>>>>>> 35ebf398 (fix: patch PEFT for Gemma4ClippableLinear in loader checkpoint path) _original_car = _LoraModel._create_and_replace def _patched_car( From 60f4ad4f8f74bdd2ca34f5a02dac999b9d32d02d Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 2 Apr 2026 23:37:48 +0000 Subject: [PATCH 03/24] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- unsloth/models/loader.py | 4 ---- 1 file changed, 4 deletions(-) diff --git a/unsloth/models/loader.py b/unsloth/models/loader.py index 362d74559b..1a8a3a15f7 100644 --- a/unsloth/models/loader.py +++ b/unsloth/models/loader.py @@ -1562,10 +1562,6 @@ class FastModel(FastBaseModel): if _clippable_linear_cls is not None: from peft.tuners.lora.model import LoraModel as _LoraModel -<<<<<<< HEAD - -======= ->>>>>>> 35ebf398 (fix: patch PEFT for Gemma4ClippableLinear in loader checkpoint path) _original_car = _LoraModel._create_and_replace def _patched_car( From cf563d1a51af85d67e2390c984ca93df8da35dc9 Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Sun, 5 Apr 2026 04:50:43 +0000 Subject: [PATCH 04/24] Skip llama.cpp install in Docker mode --- studio/setup.sh | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/studio/setup.sh b/studio/setup.sh index d2bd9485ba..20cc5b6ce7 100755 --- a/studio/setup.sh +++ b/studio/setup.sh @@ -585,6 +585,9 @@ fi fi # ── 7. Prefer prebuilt llama.cpp bundles before any source build path ── +if [ "$_DOCKER_NO_VENV" = true ]; then + step "llama.cpp" "skipped (Docker)" +else # begin non-Docker llama.cpp block UNSLOTH_HOME="$HOME/.unsloth" mkdir -p "$UNSLOTH_HOME" LLAMA_CPP_DIR="$UNSLOTH_HOME/llama.cpp" @@ -1068,6 +1071,7 @@ else fi } fi # end _SKIP_GGUF_BUILD check +fi # end non-Docker llama.cpp block # ── Footer ── if [ "$_LLAMA_ONLY" = "1" ]; then From 09eef9b22521dffe0ea0442c64809f2b39275ed0 Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Mon, 6 Apr 2026 16:25:07 +0000 Subject: [PATCH 05/24] split venv_t5 into venv_t5_530 and venv_t5_550 for tiered transformers 5.x support --- studio/backend/core/export/worker.py | 3 - studio/backend/core/inference/worker.py | 2 - studio/backend/core/training/worker.py | 17 +++++ studio/setup.ps1 | 83 +++++++++++++++++++++++++ studio/setup.sh | 23 +++++++ 5 files changed, 123 insertions(+), 5 deletions(-) diff --git a/studio/backend/core/export/worker.py b/studio/backend/core/export/worker.py index f77b1966c4..1be456d4d4 100644 --- a/studio/backend/core/export/worker.py +++ b/studio/backend/core/export/worker.py @@ -181,11 +181,8 @@ def _setup_log_capture(resp_queue: Any) -> None: def _activate_transformers_version(model_name: str) -> None: """Activate the correct transformers version BEFORE any ML imports.""" - # Ensure backend is on path for utils imports - backend_path = str(Path(__file__).resolve().parent.parent.parent) if backend_path not in sys.path: sys.path.insert(0, backend_path) - from utils.transformers_version import activate_transformers_for_subprocess activate_transformers_for_subprocess(model_name) diff --git a/studio/backend/core/inference/worker.py b/studio/backend/core/inference/worker.py index fbcce276ba..4f86f99ded 100644 --- a/studio/backend/core/inference/worker.py +++ b/studio/backend/core/inference/worker.py @@ -35,8 +35,6 @@ from utils.hardware import apply_gpu_ids def _activate_transformers_version(model_name: str) -> None: """Activate the correct transformers version BEFORE any ML imports.""" - # Ensure backend is on path for utils imports - backend_path = str(Path(__file__).resolve().parent.parent.parent) if backend_path not in sys.path: sys.path.insert(0, backend_path) diff --git a/studio/backend/core/training/worker.py b/studio/backend/core/training/worker.py index 8ab2b5b2be..0b0a73313f 100644 --- a/studio/backend/core/training/worker.py +++ b/studio/backend/core/training/worker.py @@ -374,6 +374,7 @@ def run_training_process( ) return +<<<<<<< HEAD # ── 1a. Auto-enable trust_remote_code for NemotronH/Nano models ── # NemotronH has config parsing bugs in transformers that require # trust_remote_code=True as a workaround. Other transformers 5.x models @@ -385,6 +386,22 @@ def run_training_process( if ( any(sub in _lowered for sub in _NEMOTRON_TRUST_SUBSTRINGS) and (_lowered.startswith("unsloth/") or _lowered.startswith("nvidia/")) +======= + # ── 1a. Auto-enable trust_remote_code for unsloth/* transformers 5.x models ── + # Some newer architectures (e.g. NemotronH) have config parsing bugs in + # transformers that require trust_remote_code=True as a workaround. + # Only auto-enable for unsloth/* prefixed models (trusted source). + # Exclude Gemma 4 since it is a native transformers 5.5 model and + # trust_remote_code=True would bypass the compiler (disabling fused CE). + from utils.transformers_version import get_transformers_tier + + _lowered = model_name.lower() + _tier = get_transformers_tier(model_name) + if ( + _tier != "default" + and _lowered.startswith("unsloth/") + and _tier != "550" # Gemma 4 is native t5.5 — trust_remote_code bypasses compiler +>>>>>>> 970219a3 (split venv_t5 into venv_t5_530 and venv_t5_550 for tiered transformers 5.x support) and not config.get("trust_remote_code", False) ): config["trust_remote_code"] = True diff --git a/studio/setup.ps1 b/studio/setup.ps1 index 1ba41360c7..3469327112 100644 --- a/studio/setup.ps1 +++ b/studio/setup.ps1 @@ -1581,6 +1581,89 @@ if ($stackExit -ne 0) { exit 1 } +# ── Pre-install transformers 5.x into .venv_t5_530/ and .venv_t5_550/ ── +# Models like GLM-4.7-Flash, Qwen3 MoE need transformers>=5.3.0. +# Gemma 4 models need transformers>=5.5.0. +# Pre-install into separate directories to avoid runtime pip overhead. +# The training subprocess prepends the appropriate dir to sys.path. +Write-Host "" + +# Clean up legacy single .venv_t5 directory +$VenvT5Legacy = Join-Path $env:USERPROFILE ".unsloth\studio\.venv_t5" +if (Test-Path $VenvT5Legacy) { Remove-Item -Recurse -Force $VenvT5Legacy } + +$prevEAP_t5 = $ErrorActionPreference +$ErrorActionPreference = "Continue" + +# --- .venv_t5_530 (transformers 5.3.0) --- +substep "pre-installing transformers 5.3.0 for newer model support..." +$VenvT5_530Dir = Join-Path $env:USERPROFILE ".unsloth\studio\.venv_t5_530" +if (Test-Path $VenvT5_530Dir) { Remove-Item -Recurse -Force $VenvT5_530Dir } +New-Item -ItemType Directory -Path $VenvT5_530Dir -Force | Out-Null +foreach ($pkg in @("transformers==5.3.0", "huggingface_hub==1.8.0", "hf_xet==1.4.2")) { + if ($script:UnslothVerbose) { + Fast-Install --target $VenvT5_530Dir --no-deps $pkg + $t5PkgExit = $LASTEXITCODE + $output = "" + } else { + $output = Fast-Install --target $VenvT5_530Dir --no-deps $pkg | Out-String + $t5PkgExit = $LASTEXITCODE + } + if ($t5PkgExit -ne 0) { + Write-Host "[FAIL] Could not install $pkg into .venv_t5_530/" -ForegroundColor Red + Write-Host $output -ForegroundColor Red + $ErrorActionPreference = $prevEAP_t5 + exit 1 + } +} +if ($script:UnslothVerbose) { + Fast-Install --target $VenvT5_530Dir tiktoken + $tiktokenInstallExit = $LASTEXITCODE + $output = "" +} else { + $output = Fast-Install --target $VenvT5_530Dir tiktoken | Out-String + $tiktokenInstallExit = $LASTEXITCODE +} +if ($tiktokenInstallExit -ne 0) { + substep "Could not install tiktoken into .venv_t5_530/ -- Qwen tokenizers may fail" "Yellow" +} +step "transformers" "5.3.0 pre-installed" + +# --- .venv_t5_550 (transformers 5.5.0) --- +substep "pre-installing transformers 5.5.0 for Gemma 4 support..." +$VenvT5_550Dir = Join-Path $env:USERPROFILE ".unsloth\studio\.venv_t5_550" +if (Test-Path $VenvT5_550Dir) { Remove-Item -Recurse -Force $VenvT5_550Dir } +New-Item -ItemType Directory -Path $VenvT5_550Dir -Force | Out-Null +foreach ($pkg in @("transformers==5.5.0", "huggingface_hub==1.8.0", "hf_xet==1.4.2")) { + if ($script:UnslothVerbose) { + Fast-Install --target $VenvT5_550Dir --no-deps $pkg + $t5PkgExit = $LASTEXITCODE + $output = "" + } else { + $output = Fast-Install --target $VenvT5_550Dir --no-deps $pkg | Out-String + $t5PkgExit = $LASTEXITCODE + } + if ($t5PkgExit -ne 0) { + Write-Host "[FAIL] Could not install $pkg into .venv_t5_550/" -ForegroundColor Red + Write-Host $output -ForegroundColor Red + $ErrorActionPreference = $prevEAP_t5 + exit 1 + } +} +if ($script:UnslothVerbose) { + Fast-Install --target $VenvT5_550Dir tiktoken + $tiktokenInstallExit = $LASTEXITCODE + $output = "" +} else { + $output = Fast-Install --target $VenvT5_550Dir tiktoken | Out-String + $tiktokenInstallExit = $LASTEXITCODE +} +if ($tiktokenInstallExit -ne 0) { + substep "Could not install tiktoken into .venv_t5_550/ -- Qwen tokenizers may fail" "Yellow" +} +$ErrorActionPreference = $prevEAP_t5 +step "transformers" "5.5.0 pre-installed" + } else { step "python" "dependencies up to date" # Restore ErrorActionPreference (was lowered for pip/python section) diff --git a/studio/setup.sh b/studio/setup.sh index 20cc5b6ce7..0b9ca8383b 100755 --- a/studio/setup.sh +++ b/studio/setup.sh @@ -541,6 +541,29 @@ fi if [ "$_SKIP_PYTHON_DEPS" = false ]; then install_python_stack + + # ── 6b. Pre-install transformers 5.x into .venv_t5_530/ and .venv_t5_550/ ── + # Models like GLM-4.7-Flash, Qwen3 MoE need transformers>=5.3.0. + # Gemma 4 models need transformers>=5.5.0. + # Pre-install into separate directories to avoid runtime pip overhead. + # The training subprocess prepends the appropriate dir to sys.path. + + # Clean up legacy single .venv_t5 directory + [ -d "$STUDIO_HOME/.venv_t5" ] && rm -rf "$STUDIO_HOME/.venv_t5" + + mkdir -p "$VENV_T5_530_DIR" + run_quiet "install transformers 5.3.0" fast_install --target "$VENV_T5_530_DIR" --no-deps "transformers==5.3.0" + run_quiet "install huggingface_hub for t5_530" fast_install --target "$VENV_T5_530_DIR" --no-deps "huggingface_hub==1.8.0" + run_quiet "install hf_xet for t5_530" fast_install --target "$VENV_T5_530_DIR" --no-deps "hf_xet==1.4.2" + run_quiet "install tiktoken for t5_530" fast_install --target "$VENV_T5_530_DIR" "tiktoken" + step "transformers" "5.3.0 pre-installed" + + mkdir -p "$VENV_T5_550_DIR" + run_quiet "install transformers 5.5.0" fast_install --target "$VENV_T5_550_DIR" --no-deps "transformers==5.5.0" + run_quiet "install huggingface_hub for t5_550" fast_install --target "$VENV_T5_550_DIR" --no-deps "huggingface_hub==1.8.0" + run_quiet "install hf_xet for t5_550" fast_install --target "$VENV_T5_550_DIR" --no-deps "hf_xet==1.4.2" + run_quiet "install tiktoken for t5_550" fast_install --target "$VENV_T5_550_DIR" "tiktoken" + step "transformers" "5.5.0 pre-installed" else step "python" "dependencies up to date" verbose_substep "python deps check: installed=$_PKG_NAME@${INSTALLED_VER:-unknown} latest=${LATEST_VER:-unknown}" From ea1cce41add251d86691e0bf03aaabd08eb1bcbd Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Mon, 6 Apr 2026 17:28:55 +0000 Subject: [PATCH 06/24] fix bfloat16 crash on T4 for FORCE_FLOAT32 models and disable trust_remote_code auto-enable for native t5 models --- studio/backend/core/training/worker.py | 17 ----------------- unsloth/models/loader.py | 4 +++- 2 files changed, 3 insertions(+), 18 deletions(-) diff --git a/studio/backend/core/training/worker.py b/studio/backend/core/training/worker.py index 0b0a73313f..8ab2b5b2be 100644 --- a/studio/backend/core/training/worker.py +++ b/studio/backend/core/training/worker.py @@ -374,7 +374,6 @@ def run_training_process( ) return -<<<<<<< HEAD # ── 1a. Auto-enable trust_remote_code for NemotronH/Nano models ── # NemotronH has config parsing bugs in transformers that require # trust_remote_code=True as a workaround. Other transformers 5.x models @@ -386,22 +385,6 @@ def run_training_process( if ( any(sub in _lowered for sub in _NEMOTRON_TRUST_SUBSTRINGS) and (_lowered.startswith("unsloth/") or _lowered.startswith("nvidia/")) -======= - # ── 1a. Auto-enable trust_remote_code for unsloth/* transformers 5.x models ── - # Some newer architectures (e.g. NemotronH) have config parsing bugs in - # transformers that require trust_remote_code=True as a workaround. - # Only auto-enable for unsloth/* prefixed models (trusted source). - # Exclude Gemma 4 since it is a native transformers 5.5 model and - # trust_remote_code=True would bypass the compiler (disabling fused CE). - from utils.transformers_version import get_transformers_tier - - _lowered = model_name.lower() - _tier = get_transformers_tier(model_name) - if ( - _tier != "default" - and _lowered.startswith("unsloth/") - and _tier != "550" # Gemma 4 is native t5.5 — trust_remote_code bypasses compiler ->>>>>>> 970219a3 (split venv_t5 into venv_t5_530 and venv_t5_550 for tiered transformers 5.x support) and not config.get("trust_remote_code", False) ): config["trust_remote_code"] = True diff --git a/unsloth/models/loader.py b/unsloth/models/loader.py index 1a8a3a15f7..123d32c82c 100644 --- a/unsloth/models/loader.py +++ b/unsloth/models/loader.py @@ -1374,7 +1374,9 @@ class FastModel(FastBaseModel): or disable_name.lower() in model_types_all ) and ((dtype == torch.float16) or not SUPPORTS_BFLOAT16): os.environ["UNSLOTH_FORCE_FLOAT32"] = "1" - dtype = torch.bfloat16 # Change to bfloat16 loading + # Use bfloat16 storage where supported; fall back to float32 on + # older GPUs (e.g. T4) that lack native bfloat16 support. + dtype = torch.bfloat16 if SUPPORTS_BFLOAT16 else torch.float32 break # Apply gradient checkpointing with smart heuristics use_gradient_checkpointing = apply_unsloth_gradient_checkpointing( From ff8a65bc3fcd599a0ff2ea8633ac00c21d9dca55 Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Mon, 6 Apr 2026 17:29:22 +0000 Subject: [PATCH 07/24] revert FORCE_FLOAT32 dtype change --- unsloth/models/loader.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/unsloth/models/loader.py b/unsloth/models/loader.py index 123d32c82c..1a8a3a15f7 100644 --- a/unsloth/models/loader.py +++ b/unsloth/models/loader.py @@ -1374,9 +1374,7 @@ class FastModel(FastBaseModel): or disable_name.lower() in model_types_all ) and ((dtype == torch.float16) or not SUPPORTS_BFLOAT16): os.environ["UNSLOTH_FORCE_FLOAT32"] = "1" - # Use bfloat16 storage where supported; fall back to float32 on - # older GPUs (e.g. T4) that lack native bfloat16 support. - dtype = torch.bfloat16 if SUPPORTS_BFLOAT16 else torch.float32 + dtype = torch.bfloat16 # Change to bfloat16 loading break # Apply gradient checkpointing with smart heuristics use_gradient_checkpointing = apply_unsloth_gradient_checkpointing( From fd098a3f3a22d582c606f92afe7c1a0d39f3c823 Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Mon, 6 Apr 2026 18:20:08 +0000 Subject: [PATCH 08/24] restrict trust_remote_code auto-enable to Nemotron models only --- studio/backend/core/inference/worker.py | 52 +++++++-- studio/backend/core/training/worker.py | 139 ++++++++++++++++++++++-- 2 files changed, 173 insertions(+), 18 deletions(-) diff --git a/studio/backend/core/inference/worker.py b/studio/backend/core/inference/worker.py index 4f86f99ded..1010e56dac 100644 --- a/studio/backend/core/inference/worker.py +++ b/studio/backend/core/inference/worker.py @@ -34,13 +34,50 @@ from utils.hardware import apply_gpu_ids def _activate_transformers_version(model_name: str) -> None: - """Activate the correct transformers version BEFORE any ML imports.""" + """Activate the correct transformers version BEFORE any ML imports. + + Uses get_transformers_tier() to decide between .venv_t5_550/ (5.5.0), + .venv_t5_530/ (5.3.0), or the default 4.57.x. + """ + # Ensure backend is on path for utils imports + backend_path = str(Path(__file__).resolve().parent.parent.parent) if backend_path not in sys.path: sys.path.insert(0, backend_path) - from utils.transformers_version import activate_transformers_for_subprocess + from utils.transformers_version import ( + get_transformers_tier, + _resolve_base_model, + _ensure_venv_t5_530_exists, + _ensure_venv_t5_550_exists, + _VENV_T5_530_DIR, + _VENV_T5_550_DIR, + ) - activate_transformers_for_subprocess(model_name) + resolved = _resolve_base_model(model_name) + tier = get_transformers_tier(resolved) + + if tier == "550": + if not _ensure_venv_t5_550_exists(): + raise RuntimeError( + f"Cannot activate transformers 5.5.0: .venv_t5_550 missing at {_VENV_T5_550_DIR}" + ) + if _VENV_T5_550_DIR not in sys.path: + sys.path.insert(0, _VENV_T5_550_DIR) + logger.info("Activated transformers 5.5.0 from %s", _VENV_T5_550_DIR) + _pp = os.environ.get("PYTHONPATH", "") + os.environ["PYTHONPATH"] = _VENV_T5_550_DIR + (os.pathsep + _pp if _pp else "") + elif tier == "530": + if not _ensure_venv_t5_530_exists(): + raise RuntimeError( + f"Cannot activate transformers 5.3.0: .venv_t5_530 missing at {_VENV_T5_530_DIR}" + ) + if _VENV_T5_530_DIR not in sys.path: + sys.path.insert(0, _VENV_T5_530_DIR) + logger.info("Activated transformers 5.3.0 from %s", _VENV_T5_530_DIR) + _pp = os.environ.get("PYTHONPATH", "") + os.environ["PYTHONPATH"] = _VENV_T5_530_DIR + (os.pathsep + _pp if _pp else "") + else: + logger.info("Using default transformers (4.57.x) for %s", model_name) def _decode_image(image_base64: str): @@ -285,18 +322,13 @@ def _handle_load(backend, config: dict, resp_queue: Any) -> None: except Exception as e: logger.warning("Could not read adapter_config.json: %s", e) - # Auto-enable trust_remote_code for NemotronH/Nano models only. + # Auto-enable trust_remote_code for Nemotron models only. # NemotronH has config parsing bugs requiring trust_remote_code=True. # Other transformers 5.x models are native and do NOT need it. - # NOTE: Must NOT match Llama-Nemotron (standard Llama architecture). - _NEMOTRON_TRUST_SUBSTRINGS = ("nemotron_h", "nemotron-h", "nemotron-3-nano") trust_remote_code = config.get("trust_remote_code", False) if not trust_remote_code: model_name = config["model_name"] - _mn_lower = model_name.lower() - if any(sub in _mn_lower for sub in _NEMOTRON_TRUST_SUBSTRINGS) and ( - _mn_lower.startswith("unsloth/") or _mn_lower.startswith("nvidia/") - ): + if "nemotron" in model_name.lower(): trust_remote_code = True logger.info( "Auto-enabled trust_remote_code for Nemotron model: %s", diff --git a/studio/backend/core/training/worker.py b/studio/backend/core/training/worker.py index 8ab2b5b2be..ec6ba1837e 100644 --- a/studio/backend/core/training/worker.py +++ b/studio/backend/core/training/worker.py @@ -64,6 +64,97 @@ def _model_wants_causal_conv1d(model_name: str) -> bool: ) +def _causal_conv1d_platform_tag() -> str | None: + machine = platform.machine().lower() + if sys.platform.startswith("linux"): + if machine in {"x86_64", "amd64"}: + return "linux_x86_64" + if machine in {"aarch64", "arm64"}: + return "linux_aarch64" + return None + # No prebuilt wheels published for macOS or Windows + return None + + +def _probe_causal_conv1d_env() -> dict[str, str] | None: + try: + probe = _sp.run( + [ + sys.executable, + "-c", + ( + "import json, sys, re, torch; " + "parts = torch.__version__.split('+', 1)[0].split('.')[:2]; " + "minor = re.sub(r'[^0-9].*', '', parts[1]) if len(parts) > 1 else '0'; " + "torch_mm = parts[0] + '.' + minor; " + "print(json.dumps({" + "'python_tag': f'cp{sys.version_info.major}{sys.version_info.minor}', " + "'torch_mm': torch_mm, " + "'cuda_major': str(int(str(torch.version.cuda).split('.', 1)[0])) if torch.version.cuda else '', " + "'cxx11abi': str(torch._C._GLIBCXX_USE_CXX11_ABI).upper()" + "}))" + ), + ], + stdout = _sp.PIPE, + stderr = _sp.PIPE, + text = True, + timeout = 30, + ) + except _sp.TimeoutExpired: + logger.warning("Torch environment probe timed out after 30s") + return None + if probe.returncode != 0: + logger.warning( + "Failed to probe torch environment for causal-conv1d wheel:\n%s", + probe.stdout, + ) + return None + + try: + return json.loads(probe.stdout.strip()) + except json.JSONDecodeError: + logger.warning( + "Failed to parse torch environment probe output: %s", probe.stdout + ) + return None + + +def _direct_wheel_url( + *, + filename_prefix: str, + package_version: str, + release_tag: str, + release_base_url: str, + env: dict[str, str] | None = None, +) -> str | None: + env = env or _probe_causal_conv1d_env() + platform_tag = _causal_conv1d_platform_tag() + if env is None or platform_tag is None or not env.get("cuda_major"): + return None + + filename = ( + f"{filename_prefix}-{package_version}" + f"+cu{env['cuda_major']}torch{env['torch_mm']}" + f"cxx11abi{env['cxx11abi']}-{env['python_tag']}-{env['python_tag']}-{platform_tag}.whl" + ) + return f"{release_base_url}/{release_tag}/{filename}" + + +def _url_exists(url: str) -> bool: + try: + request = urllib.request.Request(url, method = "HEAD") + with urllib.request.urlopen(request, timeout = 10): + return True + except urllib.error.HTTPError as exc: + if exc.code == 404: + return False + logger.warning("Unexpected HTTP error while probing %s: %s", url, exc) + return False + except Exception as exc: + logger.warning("Failed to probe %s: %s", url, exc) + return False + + def _install_package_wheel_first( *, event_queue: Any, @@ -316,15 +407,50 @@ def _ensure_flash_attn_for_long_context(event_queue: Any, max_seq_length: int) - def _activate_transformers_version(model_name: str) -> None: - """Activate the correct transformers version BEFORE any ML imports.""" + """Activate the correct transformers version BEFORE any ML imports. + + Uses get_transformers_tier() to decide between .venv_t5_550/ (5.5.0), + .venv_t5_530/ (5.3.0), or the default 4.57.x. + """ # Ensure backend is on path for utils imports backend_path = str(Path(__file__).resolve().parent.parent.parent) if backend_path not in sys.path: sys.path.insert(0, backend_path) - from utils.transformers_version import activate_transformers_for_subprocess + from utils.transformers_version import ( + get_transformers_tier, + _resolve_base_model, + _ensure_venv_t5_530_exists, + _ensure_venv_t5_550_exists, + _VENV_T5_530_DIR, + _VENV_T5_550_DIR, + ) - activate_transformers_for_subprocess(model_name) + resolved = _resolve_base_model(model_name) + tier = get_transformers_tier(resolved) + + if tier == "550": + if not _ensure_venv_t5_550_exists(): + raise RuntimeError( + f"Cannot activate transformers 5.5.0: .venv_t5_550 missing at {_VENV_T5_550_DIR}" + ) + if _VENV_T5_550_DIR not in sys.path: + sys.path.insert(0, _VENV_T5_550_DIR) + logger.info("Activated transformers 5.5.0 from %s", _VENV_T5_550_DIR) + _pp = os.environ.get("PYTHONPATH", "") + os.environ["PYTHONPATH"] = _VENV_T5_550_DIR + (os.pathsep + _pp if _pp else "") + elif tier == "530": + if not _ensure_venv_t5_530_exists(): + raise RuntimeError( + f"Cannot activate transformers 5.3.0: .venv_t5_530 missing at {_VENV_T5_530_DIR}" + ) + if _VENV_T5_530_DIR not in sys.path: + sys.path.insert(0, _VENV_T5_530_DIR) + logger.info("Activated transformers 5.3.0 from %s", _VENV_T5_530_DIR) + _pp = os.environ.get("PYTHONPATH", "") + os.environ["PYTHONPATH"] = _VENV_T5_530_DIR + (os.pathsep + _pp if _pp else "") + else: + logger.info("Using default transformers (4.57.x) for %s", model_name) def run_training_process( @@ -374,17 +500,14 @@ def run_training_process( ) return - # ── 1a. Auto-enable trust_remote_code for NemotronH/Nano models ── + # ── 1a. Auto-enable trust_remote_code for Nemotron models ── # NemotronH has config parsing bugs in transformers that require # trust_remote_code=True as a workaround. Other transformers 5.x models # (Qwen3.5, Gemma 4, etc.) are native and do NOT need it — enabling it # bypasses the compiler (disabling fused CE). - # NOTE: Must NOT match Llama-Nemotron (standard Llama architecture). - _NEMOTRON_TRUST_SUBSTRINGS = ("nemotron_h", "nemotron-h", "nemotron-3-nano") _lowered = model_name.lower() if ( - any(sub in _lowered for sub in _NEMOTRON_TRUST_SUBSTRINGS) - and (_lowered.startswith("unsloth/") or _lowered.startswith("nvidia/")) + "nemotron" in _lowered and not config.get("trust_remote_code", False) ): config["trust_remote_code"] = True From 0586aefddeae0d0f59757441fa5375895af3d0af Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 6 Apr 2026 19:09:39 +0000 Subject: [PATCH 09/24] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- studio/backend/core/training/worker.py | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/studio/backend/core/training/worker.py b/studio/backend/core/training/worker.py index ec6ba1837e..2c4672231a 100644 --- a/studio/backend/core/training/worker.py +++ b/studio/backend/core/training/worker.py @@ -506,10 +506,7 @@ def run_training_process( # (Qwen3.5, Gemma 4, etc.) are native and do NOT need it — enabling it # bypasses the compiler (disabling fused CE). _lowered = model_name.lower() - if ( - "nemotron" in _lowered - and not config.get("trust_remote_code", False) - ): + if "nemotron" in _lowered and not config.get("trust_remote_code", False): config["trust_remote_code"] = True logger.info( "Auto-enabled trust_remote_code for Nemotron model: %s", From 8cc132dc6e3adae6a11d0b7ccc8b0c9b758545e5 Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Mon, 6 Apr 2026 19:40:11 +0000 Subject: [PATCH 10/24] use config.json model_type for tier detection, add unsloth/nvidia namespace guard --- studio/backend/core/inference/worker.py | 6 +- studio/backend/core/training/worker.py | 6 +- .../tests/test_transformers_version.py | 25 ++- studio/backend/utils/transformers_version.py | 161 ++++++++---------- 4 files changed, 99 insertions(+), 99 deletions(-) diff --git a/studio/backend/core/inference/worker.py b/studio/backend/core/inference/worker.py index 1010e56dac..506e631c51 100644 --- a/studio/backend/core/inference/worker.py +++ b/studio/backend/core/inference/worker.py @@ -328,7 +328,11 @@ def _handle_load(backend, config: dict, resp_queue: Any) -> None: trust_remote_code = config.get("trust_remote_code", False) if not trust_remote_code: model_name = config["model_name"] - if "nemotron" in model_name.lower(): + _mn_lower = model_name.lower() + if ( + "nemotron" in _mn_lower + and (_mn_lower.startswith("unsloth/") or _mn_lower.startswith("nvidia/")) + ): trust_remote_code = True logger.info( "Auto-enabled trust_remote_code for Nemotron model: %s", diff --git a/studio/backend/core/training/worker.py b/studio/backend/core/training/worker.py index 2c4672231a..edd88cc10f 100644 --- a/studio/backend/core/training/worker.py +++ b/studio/backend/core/training/worker.py @@ -506,7 +506,11 @@ def run_training_process( # (Qwen3.5, Gemma 4, etc.) are native and do NOT need it — enabling it # bypasses the compiler (disabling fused CE). _lowered = model_name.lower() - if "nemotron" in _lowered and not config.get("trust_remote_code", False): + if ( + "nemotron" in _lowered + and (_lowered.startswith("unsloth/") or _lowered.startswith("nvidia/")) + and not config.get("trust_remote_code", False) + ): config["trust_remote_code"] = True logger.info( "Auto-enabled trust_remote_code for Nemotron model: %s", diff --git a/studio/backend/tests/test_transformers_version.py b/studio/backend/tests/test_transformers_version.py index c031c2fea3..609a154a9a 100644 --- a/studio/backend/tests/test_transformers_version.py +++ b/studio/backend/tests/test_transformers_version.py @@ -32,8 +32,9 @@ from utils.transformers_version import ( _resolve_base_model, _check_tokenizer_config_needs_v5, _check_config_needs_550, + _get_config_json, _tokenizer_class_cache, - _config_needs_550_cache, + _config_json_cache, needs_transformers_5, get_transformers_tier, ) @@ -202,7 +203,7 @@ class TestCheckConfigNeeds550: """Tests for _check_config_needs_550() local config.json checks.""" def setup_method(self): - _config_needs_550_cache.clear() + _config_json_cache.clear() def test_gemma4_architecture(self, tmp_path: Path): """config.json with Gemma4ForConditionalGeneration should return True.""" @@ -242,8 +243,8 @@ class TestCheckConfigNeeds550: key = str(tmp_path) _check_config_needs_550(key) - assert key in _config_needs_550_cache - assert _config_needs_550_cache[key] is True + assert key in _config_json_cache + assert _config_json_cache[key] is not None def test_local_file_skips_network(self, tmp_path: Path): """When local config.json exists, no network request should be made.""" @@ -265,7 +266,7 @@ class TestGetTransformersTier: def setup_method(self): _tokenizer_class_cache.clear() - _config_needs_550_cache.clear() + _config_json_cache.clear() def test_gemma4_substring_returns_550(self): assert get_transformers_tier("google/gemma-4-E2B-it") == "550" @@ -317,6 +318,20 @@ class TestGetTransformersTier: # This shouldn't happen in practice, but verifies priority assert get_transformers_tier("gemma-4-model") == "550" + def test_config_json_model_type_530(self, tmp_path: Path): + """Local checkpoint with qwen3_moe model_type → 530.""" + cfg = {"model_type": "qwen3_moe", "architectures": ["Qwen3MoeForCausalLM"]} + (tmp_path / "config.json").write_text(json.dumps(cfg)) + + assert get_transformers_tier(str(tmp_path)) == "530" + + def test_config_json_model_type_glm4_moe(self, tmp_path: Path): + """Local checkpoint with glm4_moe model_type → 530.""" + cfg = {"model_type": "glm4_moe", "architectures": ["Glm4MoeForCausalLM"]} + (tmp_path / "config.json").write_text(json.dumps(cfg)) + + assert get_transformers_tier(str(tmp_path)) == "530" + def test_needs_transformers_5_compat(self): """needs_transformers_5 should return True for both 530 and 550 models.""" assert needs_transformers_5("google/gemma-4-E2B-it") is True diff --git a/studio/backend/utils/transformers_version.py b/studio/backend/utils/transformers_version.py index 36c3a4c22d..5ae92f2df1 100644 --- a/studio/backend/utils/transformers_version.py +++ b/studio/backend/utils/transformers_version.py @@ -61,14 +61,25 @@ TRANSFORMERS_550_MODEL_SUBSTRINGS: tuple[str, ...] = ( "gemma4", # Gemma-4 alternate naming ) -# Architecture classes / model_type values that require transformers 5.5.0. -# Checked via config.json (local or HuggingFace). +# Architecture classes that require transformers 5.5.0. _TRANSFORMERS_550_ARCHITECTURES: set[str] = { "Gemma4ForConditionalGeneration", } + +# model_type values (from config.json) → tier mapping. _TRANSFORMERS_550_MODEL_TYPES: set[str] = { "gemma4", } +_TRANSFORMERS_530_MODEL_TYPES: set[str] = { + "qwen3_moe", + "qwen3_5_moe", + "qwen3_vl_moe", + "qwen3_next", + "deepseek_v3_moe", + "glm4_moe", + "glm4_moe_lite", + "ministral", +} # Tokenizer classes that only exist in transformers>=5.x _TRANSFORMERS_5_TOKENIZER_CLASSES: set[str] = { @@ -78,15 +89,14 @@ _TRANSFORMERS_5_TOKENIZER_CLASSES: set[str] = { # Cache for dynamic tokenizer_config.json lookups to avoid repeated fetches _tokenizer_class_cache: dict[str, bool] = {} -# Cache for dynamic config.json lookups (architecture/model_type checks) -_config_needs_550_cache: dict[str, bool] = {} +# Cache for config.json lookups (returns the parsed dict or None) +_config_json_cache: dict[str, dict | None] = {} # Versions TRANSFORMERS_550_VERSION = "5.5.0" TRANSFORMERS_530_VERSION = "5.3.0" TRANSFORMERS_DEFAULT_VERSION = "4.57.6" -# Backwards-compat alias — points to 5.5.0 (the highest 5.x tier). -# Consumers should prefer TRANSFORMERS_530_VERSION / TRANSFORMERS_550_VERSION. +# Backwards-compat alias used by other modules TRANSFORMERS_5_VERSION = TRANSFORMERS_550_VERSION # Pre-installed directories — created by setup.sh / setup.ps1 @@ -96,45 +106,6 @@ _VENV_T5_550_DIR = str(Path.home() / ".unsloth" / "studio" / ".venv_t5_550") _VENV_T5_DIR = _VENV_T5_550_DIR -def activate_transformers_for_subprocess(model_name: str) -> None: - """Activate the correct transformers version in a subprocess worker. - - Call this BEFORE any ML imports. Resolves LoRA adapters to their base - model, determines the required tier, and prepends the appropriate - ``.venv_t5_*`` directory to ``sys.path``. Also propagates the path - via ``PYTHONPATH`` for child processes (e.g. GGUF converter). - - Used by training, inference, and export workers. - """ - resolved = _resolve_base_model(model_name) - tier = get_transformers_tier(resolved) - - if tier == "550": - if not _ensure_venv_t5_550_exists(): - raise RuntimeError( - f"Cannot activate transformers 5.5.0: " - f".venv_t5_550 missing at {_VENV_T5_550_DIR}" - ) - if _VENV_T5_550_DIR not in sys.path: - sys.path.insert(0, _VENV_T5_550_DIR) - logger.info("Activated transformers 5.5.0 from %s", _VENV_T5_550_DIR) - _pp = os.environ.get("PYTHONPATH", "") - os.environ["PYTHONPATH"] = _VENV_T5_550_DIR + (os.pathsep + _pp if _pp else "") - elif tier == "530": - if not _ensure_venv_t5_530_exists(): - raise RuntimeError( - f"Cannot activate transformers 5.3.0: " - f".venv_t5_530 missing at {_VENV_T5_530_DIR}" - ) - if _VENV_T5_530_DIR not in sys.path: - sys.path.insert(0, _VENV_T5_530_DIR) - logger.info("Activated transformers 5.3.0 from %s", _VENV_T5_530_DIR) - _pp = os.environ.get("PYTHONPATH", "") - os.environ["PYTHONPATH"] = _VENV_T5_530_DIR + (os.pathsep + _pp if _pp else "") - else: - logger.info("Using default transformers (4.57.x) for %s", model_name) - - def _resolve_base_model(model_name: str) -> str: """If *model_name* points to a LoRA adapter, return its base model. @@ -260,43 +231,28 @@ def _check_tokenizer_config_needs_v5(model_name: str) -> bool: return False -def _check_config_needs_550(model_name: str) -> bool: - """Check ``config.json`` for architectures or model_type that require - transformers 5.5.0 (e.g. Gemma 4). +_SENTINEL = object() # distinguishes "not cached" from "cached as None" - Checks locally first, then falls back to fetching from HuggingFace. - Results are cached in ``_config_needs_550_cache``. - Returns False on any error (fail-open to lower tier). + +def _get_config_json(model_name: str) -> dict | None: + """Read and cache ``config.json`` for *model_name*. + + Checks local path first, then fetches from HuggingFace. + Returns the parsed dict, or ``None`` on any error (fail-open). + The result is cached in ``_config_json_cache``. """ - if model_name in _config_needs_550_cache: - return _config_needs_550_cache[model_name] - - def _check_cfg(cfg: dict) -> bool: - archs = cfg.get("architectures", []) - if any(a in _TRANSFORMERS_550_ARCHITECTURES for a in archs): - return True - if cfg.get("model_type") in _TRANSFORMERS_550_MODEL_TYPES: - return True - return False + cached = _config_json_cache.get(model_name, _SENTINEL) + if cached is not _SENTINEL: + return cached # --- Check local config.json first ------------------------------------ - local_path = Path(model_name) - local_cfg = local_path / "config.json" + local_cfg = Path(model_name) / "config.json" if local_cfg.is_file(): try: with open(local_cfg) as f: cfg = json.load(f) - result = _check_cfg(cfg) - if result: - logger.info( - "Local config.json check: %s needs transformers 5.5.0 " - "(architectures=%s, model_type=%s)", - model_name, - cfg.get("architectures", []), - cfg.get("model_type"), - ) - _config_needs_550_cache[model_name] = result - return result + _config_json_cache[model_name] = cfg + return cfg except Exception as exc: logger.debug("Could not read %s: %s", local_cfg, exc) @@ -308,21 +264,26 @@ def _check_config_needs_550(model_name: str) -> bool: req = urllib.request.Request(url, headers = {"User-Agent": "unsloth-studio"}) with urllib.request.urlopen(req, timeout = 10) as resp: cfg = json.loads(resp.read().decode()) - result = _check_cfg(cfg) - if result: - logger.info( - "Dynamic config.json check: %s needs transformers 5.5.0 " - "(architectures=%s, model_type=%s)", - model_name, - cfg.get("architectures", []), - cfg.get("model_type"), - ) - _config_needs_550_cache[model_name] = result - return result + _config_json_cache[model_name] = cfg + return cfg except Exception as exc: - logger.debug("Could not fetch config.json for '%s': %s", model_name, exc) - _config_needs_550_cache[model_name] = False + logger.debug( + "Could not fetch config.json for '%s': %s", model_name, exc + ) + _config_json_cache[model_name] = None + return None + + +def _check_config_needs_550(model_name: str) -> bool: + """Check ``config.json`` for architectures or model_type that require + transformers 5.5.0. Uses the shared ``_get_config_json`` cache.""" + cfg = _get_config_json(model_name) + if cfg is None: return False + archs = cfg.get("architectures", []) + if any(a in _TRANSFORMERS_550_ARCHITECTURES for a in archs): + return True + return cfg.get("model_type") in _TRANSFORMERS_550_MODEL_TYPES def get_transformers_tier(model_name: str) -> str: @@ -332,19 +293,35 @@ def get_transformers_tier(model_name: str) -> str: ``"530"`` for models needing transformers 5.3.0 (e.g. Ministral-3, Qwen3 MoE), or ``"default"`` for everything else (4.57.x). - The 5.5.0 check runs first, then 5.3.0. + Fast path: substring checks (no I/O) for both tiers run first. + Slow path: single config.json fetch (cached) checks model_type for + both tiers, then tokenizer_config.json as final fallback. """ lowered = model_name.lower() - # --- Fast substring checks (no I/O) ------------------------------------ + # --- Fast substring checks (no I/O) ----------------------------------- if any(sub in lowered for sub in TRANSFORMERS_550_MODEL_SUBSTRINGS): return "550" if any(sub in lowered for sub in TRANSFORMERS_5_MODEL_SUBSTRINGS): return "530" - # --- Slow config fallbacks (local file first, then network) ----------- - if _check_config_needs_550(model_name): - return "550" + # --- config.json model_type / architecture check (single fetch) ------- + cfg = _get_config_json(model_name) + if cfg is not None: + model_type = cfg.get("model_type", "") + archs = cfg.get("architectures", []) + + # Check 5.5.0 first + if model_type in _TRANSFORMERS_550_MODEL_TYPES: + return "550" + if any(a in _TRANSFORMERS_550_ARCHITECTURES for a in archs): + return "550" + + # Check 5.3.0 + if model_type in _TRANSFORMERS_530_MODEL_TYPES: + return "530" + + # --- Final fallback: tokenizer_config.json for 5.3.0 ------------------ if _check_tokenizer_config_needs_v5(model_name): return "530" From 332b8e9e361bef1d9f8c1442f1c625b287f200e9 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 6 Apr 2026 19:42:48 +0000 Subject: [PATCH 11/24] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- studio/backend/core/inference/worker.py | 5 ++--- studio/backend/utils/transformers_version.py | 4 +--- 2 files changed, 3 insertions(+), 6 deletions(-) diff --git a/studio/backend/core/inference/worker.py b/studio/backend/core/inference/worker.py index 506e631c51..db504bac3a 100644 --- a/studio/backend/core/inference/worker.py +++ b/studio/backend/core/inference/worker.py @@ -329,9 +329,8 @@ def _handle_load(backend, config: dict, resp_queue: Any) -> None: if not trust_remote_code: model_name = config["model_name"] _mn_lower = model_name.lower() - if ( - "nemotron" in _mn_lower - and (_mn_lower.startswith("unsloth/") or _mn_lower.startswith("nvidia/")) + if "nemotron" in _mn_lower and ( + _mn_lower.startswith("unsloth/") or _mn_lower.startswith("nvidia/") ): trust_remote_code = True logger.info( diff --git a/studio/backend/utils/transformers_version.py b/studio/backend/utils/transformers_version.py index 5ae92f2df1..656c53be1d 100644 --- a/studio/backend/utils/transformers_version.py +++ b/studio/backend/utils/transformers_version.py @@ -267,9 +267,7 @@ def _get_config_json(model_name: str) -> dict | None: _config_json_cache[model_name] = cfg return cfg except Exception as exc: - logger.debug( - "Could not fetch config.json for '%s': %s", model_name, exc - ) + logger.debug("Could not fetch config.json for '%s': %s", model_name, exc) _config_json_cache[model_name] = None return None From e7c207225887d410e1d30764af6011c4b14b1bff Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Mon, 6 Apr 2026 20:26:32 +0000 Subject: [PATCH 12/24] Revert "[pre-commit.ci] auto fixes from pre-commit.com hooks" This reverts commit fb43d468e25379f28dd2477e6c24dd60cf55c099. --- studio/backend/core/inference/worker.py | 5 +++-- studio/backend/utils/transformers_version.py | 4 +++- 2 files changed, 6 insertions(+), 3 deletions(-) diff --git a/studio/backend/core/inference/worker.py b/studio/backend/core/inference/worker.py index db504bac3a..506e631c51 100644 --- a/studio/backend/core/inference/worker.py +++ b/studio/backend/core/inference/worker.py @@ -329,8 +329,9 @@ def _handle_load(backend, config: dict, resp_queue: Any) -> None: if not trust_remote_code: model_name = config["model_name"] _mn_lower = model_name.lower() - if "nemotron" in _mn_lower and ( - _mn_lower.startswith("unsloth/") or _mn_lower.startswith("nvidia/") + if ( + "nemotron" in _mn_lower + and (_mn_lower.startswith("unsloth/") or _mn_lower.startswith("nvidia/")) ): trust_remote_code = True logger.info( diff --git a/studio/backend/utils/transformers_version.py b/studio/backend/utils/transformers_version.py index 656c53be1d..5ae92f2df1 100644 --- a/studio/backend/utils/transformers_version.py +++ b/studio/backend/utils/transformers_version.py @@ -267,7 +267,9 @@ def _get_config_json(model_name: str) -> dict | None: _config_json_cache[model_name] = cfg return cfg except Exception as exc: - logger.debug("Could not fetch config.json for '%s': %s", model_name, exc) + logger.debug( + "Could not fetch config.json for '%s': %s", model_name, exc + ) _config_json_cache[model_name] = None return None From cef87885abd65d81bb42607189459be8e738496c Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Mon, 6 Apr 2026 20:26:32 +0000 Subject: [PATCH 13/24] Revert "use config.json model_type for tier detection, add unsloth/nvidia namespace guard" This reverts commit fc49ae24531780a658049e6c238f146960f466b6. --- studio/backend/core/inference/worker.py | 6 +- studio/backend/core/training/worker.py | 6 +- .../tests/test_transformers_version.py | 25 +--- studio/backend/utils/transformers_version.py | 121 ++++++++---------- 4 files changed, 59 insertions(+), 99 deletions(-) diff --git a/studio/backend/core/inference/worker.py b/studio/backend/core/inference/worker.py index 506e631c51..1010e56dac 100644 --- a/studio/backend/core/inference/worker.py +++ b/studio/backend/core/inference/worker.py @@ -328,11 +328,7 @@ def _handle_load(backend, config: dict, resp_queue: Any) -> None: trust_remote_code = config.get("trust_remote_code", False) if not trust_remote_code: model_name = config["model_name"] - _mn_lower = model_name.lower() - if ( - "nemotron" in _mn_lower - and (_mn_lower.startswith("unsloth/") or _mn_lower.startswith("nvidia/")) - ): + if "nemotron" in model_name.lower(): trust_remote_code = True logger.info( "Auto-enabled trust_remote_code for Nemotron model: %s", diff --git a/studio/backend/core/training/worker.py b/studio/backend/core/training/worker.py index edd88cc10f..2c4672231a 100644 --- a/studio/backend/core/training/worker.py +++ b/studio/backend/core/training/worker.py @@ -506,11 +506,7 @@ def run_training_process( # (Qwen3.5, Gemma 4, etc.) are native and do NOT need it — enabling it # bypasses the compiler (disabling fused CE). _lowered = model_name.lower() - if ( - "nemotron" in _lowered - and (_lowered.startswith("unsloth/") or _lowered.startswith("nvidia/")) - and not config.get("trust_remote_code", False) - ): + if "nemotron" in _lowered and not config.get("trust_remote_code", False): config["trust_remote_code"] = True logger.info( "Auto-enabled trust_remote_code for Nemotron model: %s", diff --git a/studio/backend/tests/test_transformers_version.py b/studio/backend/tests/test_transformers_version.py index 609a154a9a..c031c2fea3 100644 --- a/studio/backend/tests/test_transformers_version.py +++ b/studio/backend/tests/test_transformers_version.py @@ -32,9 +32,8 @@ from utils.transformers_version import ( _resolve_base_model, _check_tokenizer_config_needs_v5, _check_config_needs_550, - _get_config_json, _tokenizer_class_cache, - _config_json_cache, + _config_needs_550_cache, needs_transformers_5, get_transformers_tier, ) @@ -203,7 +202,7 @@ class TestCheckConfigNeeds550: """Tests for _check_config_needs_550() local config.json checks.""" def setup_method(self): - _config_json_cache.clear() + _config_needs_550_cache.clear() def test_gemma4_architecture(self, tmp_path: Path): """config.json with Gemma4ForConditionalGeneration should return True.""" @@ -243,8 +242,8 @@ class TestCheckConfigNeeds550: key = str(tmp_path) _check_config_needs_550(key) - assert key in _config_json_cache - assert _config_json_cache[key] is not None + assert key in _config_needs_550_cache + assert _config_needs_550_cache[key] is True def test_local_file_skips_network(self, tmp_path: Path): """When local config.json exists, no network request should be made.""" @@ -266,7 +265,7 @@ class TestGetTransformersTier: def setup_method(self): _tokenizer_class_cache.clear() - _config_json_cache.clear() + _config_needs_550_cache.clear() def test_gemma4_substring_returns_550(self): assert get_transformers_tier("google/gemma-4-E2B-it") == "550" @@ -318,20 +317,6 @@ class TestGetTransformersTier: # This shouldn't happen in practice, but verifies priority assert get_transformers_tier("gemma-4-model") == "550" - def test_config_json_model_type_530(self, tmp_path: Path): - """Local checkpoint with qwen3_moe model_type → 530.""" - cfg = {"model_type": "qwen3_moe", "architectures": ["Qwen3MoeForCausalLM"]} - (tmp_path / "config.json").write_text(json.dumps(cfg)) - - assert get_transformers_tier(str(tmp_path)) == "530" - - def test_config_json_model_type_glm4_moe(self, tmp_path: Path): - """Local checkpoint with glm4_moe model_type → 530.""" - cfg = {"model_type": "glm4_moe", "architectures": ["Glm4MoeForCausalLM"]} - (tmp_path / "config.json").write_text(json.dumps(cfg)) - - assert get_transformers_tier(str(tmp_path)) == "530" - def test_needs_transformers_5_compat(self): """needs_transformers_5 should return True for both 530 and 550 models.""" assert needs_transformers_5("google/gemma-4-E2B-it") is True diff --git a/studio/backend/utils/transformers_version.py b/studio/backend/utils/transformers_version.py index 5ae92f2df1..826f26c3e0 100644 --- a/studio/backend/utils/transformers_version.py +++ b/studio/backend/utils/transformers_version.py @@ -61,25 +61,14 @@ TRANSFORMERS_550_MODEL_SUBSTRINGS: tuple[str, ...] = ( "gemma4", # Gemma-4 alternate naming ) -# Architecture classes that require transformers 5.5.0. +# Architecture classes / model_type values that require transformers 5.5.0. +# Checked via config.json (local or HuggingFace). _TRANSFORMERS_550_ARCHITECTURES: set[str] = { "Gemma4ForConditionalGeneration", } - -# model_type values (from config.json) → tier mapping. _TRANSFORMERS_550_MODEL_TYPES: set[str] = { "gemma4", } -_TRANSFORMERS_530_MODEL_TYPES: set[str] = { - "qwen3_moe", - "qwen3_5_moe", - "qwen3_vl_moe", - "qwen3_next", - "deepseek_v3_moe", - "glm4_moe", - "glm4_moe_lite", - "ministral", -} # Tokenizer classes that only exist in transformers>=5.x _TRANSFORMERS_5_TOKENIZER_CLASSES: set[str] = { @@ -89,8 +78,8 @@ _TRANSFORMERS_5_TOKENIZER_CLASSES: set[str] = { # Cache for dynamic tokenizer_config.json lookups to avoid repeated fetches _tokenizer_class_cache: dict[str, bool] = {} -# Cache for config.json lookups (returns the parsed dict or None) -_config_json_cache: dict[str, dict | None] = {} +# Cache for dynamic config.json lookups (architecture/model_type checks) +_config_needs_550_cache: dict[str, bool] = {} # Versions TRANSFORMERS_550_VERSION = "5.5.0" @@ -231,28 +220,43 @@ def _check_tokenizer_config_needs_v5(model_name: str) -> bool: return False -_SENTINEL = object() # distinguishes "not cached" from "cached as None" +def _check_config_needs_550(model_name: str) -> bool: + """Check ``config.json`` for architectures or model_type that require + transformers 5.5.0 (e.g. Gemma 4). - -def _get_config_json(model_name: str) -> dict | None: - """Read and cache ``config.json`` for *model_name*. - - Checks local path first, then fetches from HuggingFace. - Returns the parsed dict, or ``None`` on any error (fail-open). - The result is cached in ``_config_json_cache``. + Checks locally first, then falls back to fetching from HuggingFace. + Results are cached in ``_config_needs_550_cache``. + Returns False on any error (fail-open to lower tier). """ - cached = _config_json_cache.get(model_name, _SENTINEL) - if cached is not _SENTINEL: - return cached + if model_name in _config_needs_550_cache: + return _config_needs_550_cache[model_name] + + def _check_cfg(cfg: dict) -> bool: + archs = cfg.get("architectures", []) + if any(a in _TRANSFORMERS_550_ARCHITECTURES for a in archs): + return True + if cfg.get("model_type") in _TRANSFORMERS_550_MODEL_TYPES: + return True + return False # --- Check local config.json first ------------------------------------ - local_cfg = Path(model_name) / "config.json" + local_path = Path(model_name) + local_cfg = local_path / "config.json" if local_cfg.is_file(): try: with open(local_cfg) as f: cfg = json.load(f) - _config_json_cache[model_name] = cfg - return cfg + result = _check_cfg(cfg) + if result: + logger.info( + "Local config.json check: %s needs transformers 5.5.0 " + "(architectures=%s, model_type=%s)", + model_name, + cfg.get("architectures", []), + cfg.get("model_type"), + ) + _config_needs_550_cache[model_name] = result + return result except Exception as exc: logger.debug("Could not read %s: %s", local_cfg, exc) @@ -264,26 +268,21 @@ def _get_config_json(model_name: str) -> dict | None: req = urllib.request.Request(url, headers = {"User-Agent": "unsloth-studio"}) with urllib.request.urlopen(req, timeout = 10) as resp: cfg = json.loads(resp.read().decode()) - _config_json_cache[model_name] = cfg - return cfg + result = _check_cfg(cfg) + if result: + logger.info( + "Dynamic config.json check: %s needs transformers 5.5.0 " + "(architectures=%s, model_type=%s)", + model_name, + cfg.get("architectures", []), + cfg.get("model_type"), + ) + _config_needs_550_cache[model_name] = result + return result except Exception as exc: - logger.debug( - "Could not fetch config.json for '%s': %s", model_name, exc - ) - _config_json_cache[model_name] = None - return None - - -def _check_config_needs_550(model_name: str) -> bool: - """Check ``config.json`` for architectures or model_type that require - transformers 5.5.0. Uses the shared ``_get_config_json`` cache.""" - cfg = _get_config_json(model_name) - if cfg is None: + logger.debug("Could not fetch config.json for '%s': %s", model_name, exc) + _config_needs_550_cache[model_name] = False return False - archs = cfg.get("architectures", []) - if any(a in _TRANSFORMERS_550_ARCHITECTURES for a in archs): - return True - return cfg.get("model_type") in _TRANSFORMERS_550_MODEL_TYPES def get_transformers_tier(model_name: str) -> str: @@ -293,35 +292,19 @@ def get_transformers_tier(model_name: str) -> str: ``"530"`` for models needing transformers 5.3.0 (e.g. Ministral-3, Qwen3 MoE), or ``"default"`` for everything else (4.57.x). - Fast path: substring checks (no I/O) for both tiers run first. - Slow path: single config.json fetch (cached) checks model_type for - both tiers, then tokenizer_config.json as final fallback. + The 5.5.0 check runs first, then 5.3.0. """ lowered = model_name.lower() - # --- Fast substring checks (no I/O) ----------------------------------- + # --- Check 5.5.0 first ------------------------------------------------ if any(sub in lowered for sub in TRANSFORMERS_550_MODEL_SUBSTRINGS): return "550" + if _check_config_needs_550(model_name): + return "550" + + # --- Check 5.3.0 ------------------------------------------------------ if any(sub in lowered for sub in TRANSFORMERS_5_MODEL_SUBSTRINGS): return "530" - - # --- config.json model_type / architecture check (single fetch) ------- - cfg = _get_config_json(model_name) - if cfg is not None: - model_type = cfg.get("model_type", "") - archs = cfg.get("architectures", []) - - # Check 5.5.0 first - if model_type in _TRANSFORMERS_550_MODEL_TYPES: - return "550" - if any(a in _TRANSFORMERS_550_ARCHITECTURES for a in archs): - return "550" - - # Check 5.3.0 - if model_type in _TRANSFORMERS_530_MODEL_TYPES: - return "530" - - # --- Final fallback: tokenizer_config.json for 5.3.0 ------------------ if _check_tokenizer_config_needs_v5(model_name): return "530" From 2efca0c43e0da6bcb368ad48f303683f68b141bd Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Mon, 6 Apr 2026 20:27:15 +0000 Subject: [PATCH 14/24] add unsloth/nvidia namespace guard to Nemotron trust_remote_code auto-enable --- studio/backend/core/inference/worker.py | 6 +++++- studio/backend/core/training/worker.py | 6 +++++- 2 files changed, 10 insertions(+), 2 deletions(-) diff --git a/studio/backend/core/inference/worker.py b/studio/backend/core/inference/worker.py index 1010e56dac..506e631c51 100644 --- a/studio/backend/core/inference/worker.py +++ b/studio/backend/core/inference/worker.py @@ -328,7 +328,11 @@ def _handle_load(backend, config: dict, resp_queue: Any) -> None: trust_remote_code = config.get("trust_remote_code", False) if not trust_remote_code: model_name = config["model_name"] - if "nemotron" in model_name.lower(): + _mn_lower = model_name.lower() + if ( + "nemotron" in _mn_lower + and (_mn_lower.startswith("unsloth/") or _mn_lower.startswith("nvidia/")) + ): trust_remote_code = True logger.info( "Auto-enabled trust_remote_code for Nemotron model: %s", diff --git a/studio/backend/core/training/worker.py b/studio/backend/core/training/worker.py index 2c4672231a..edd88cc10f 100644 --- a/studio/backend/core/training/worker.py +++ b/studio/backend/core/training/worker.py @@ -506,7 +506,11 @@ def run_training_process( # (Qwen3.5, Gemma 4, etc.) are native and do NOT need it — enabling it # bypasses the compiler (disabling fused CE). _lowered = model_name.lower() - if "nemotron" in _lowered and not config.get("trust_remote_code", False): + if ( + "nemotron" in _lowered + and (_lowered.startswith("unsloth/") or _lowered.startswith("nvidia/")) + and not config.get("trust_remote_code", False) + ): config["trust_remote_code"] = True logger.info( "Auto-enabled trust_remote_code for Nemotron model: %s", From ee47f7c4f48d81121f6aecfdaaff965bb8457d50 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 6 Apr 2026 20:27:25 +0000 Subject: [PATCH 15/24] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- studio/backend/core/inference/worker.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/studio/backend/core/inference/worker.py b/studio/backend/core/inference/worker.py index 506e631c51..db504bac3a 100644 --- a/studio/backend/core/inference/worker.py +++ b/studio/backend/core/inference/worker.py @@ -329,9 +329,8 @@ def _handle_load(backend, config: dict, resp_queue: Any) -> None: if not trust_remote_code: model_name = config["model_name"] _mn_lower = model_name.lower() - if ( - "nemotron" in _mn_lower - and (_mn_lower.startswith("unsloth/") or _mn_lower.startswith("nvidia/")) + if "nemotron" in _mn_lower and ( + _mn_lower.startswith("unsloth/") or _mn_lower.startswith("nvidia/") ): trust_remote_code = True logger.info( From ed694d67eeebcc642fab006856ceb4022684f819 Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Mon, 6 Apr 2026 20:31:06 +0000 Subject: [PATCH 16/24] reorder tier checks: all substring matches before config.json fetches --- studio/backend/utils/transformers_version.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/studio/backend/utils/transformers_version.py b/studio/backend/utils/transformers_version.py index 826f26c3e0..7e18086dca 100644 --- a/studio/backend/utils/transformers_version.py +++ b/studio/backend/utils/transformers_version.py @@ -296,15 +296,15 @@ def get_transformers_tier(model_name: str) -> str: """ lowered = model_name.lower() - # --- Check 5.5.0 first ------------------------------------------------ + # --- Fast substring checks (no I/O) ------------------------------------ if any(sub in lowered for sub in TRANSFORMERS_550_MODEL_SUBSTRINGS): return "550" - if _check_config_needs_550(model_name): - return "550" - - # --- Check 5.3.0 ------------------------------------------------------ if any(sub in lowered for sub in TRANSFORMERS_5_MODEL_SUBSTRINGS): return "530" + + # --- Slow config fallbacks (local file first, then network) ----------- + if _check_config_needs_550(model_name): + return "550" if _check_tokenizer_config_needs_v5(model_name): return "530" From 74ca59487f4ced993c441d1c0ae474c2c7e3ae8b Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Mon, 6 Apr 2026 22:35:50 +0000 Subject: [PATCH 17/24] extract shared activate_transformers_for_subprocess into transformers_version.py --- studio/backend/core/export/worker.py | 16 ++------ studio/backend/core/inference/worker.py | 41 ++----------------- studio/backend/core/training/worker.py | 41 ++----------------- studio/backend/utils/transformers_version.py | 43 ++++++++++++++++++++ 4 files changed, 52 insertions(+), 89 deletions(-) diff --git a/studio/backend/core/export/worker.py b/studio/backend/core/export/worker.py index 1be456d4d4..80b05aca79 100644 --- a/studio/backend/core/export/worker.py +++ b/studio/backend/core/export/worker.py @@ -181,8 +181,11 @@ def _setup_log_capture(resp_queue: Any) -> None: def _activate_transformers_version(model_name: str) -> None: """Activate the correct transformers version BEFORE any ML imports.""" + # Ensure backend is on path for utils imports + backend_path = str(Path(__file__).resolve().parent.parent.parent) if backend_path not in sys.path: sys.path.insert(0, backend_path) + from utils.transformers_version import activate_transformers_for_subprocess activate_transformers_for_subprocess(model_name) @@ -203,19 +206,6 @@ def _handle_load(backend, cmd: dict, resp_queue: Any) -> None: load_in_4bit = cmd.get("load_in_4bit", True) trust_remote_code = cmd.get("trust_remote_code", False) - # Auto-enable trust_remote_code for NemotronH/Nano models. - if not trust_remote_code: - _NEMOTRON_TRUST_SUBSTRINGS = ("nemotron_h", "nemotron-h", "nemotron-3-nano") - _cp_lower = checkpoint_path.lower() - if any(sub in _cp_lower for sub in _NEMOTRON_TRUST_SUBSTRINGS) and ( - _cp_lower.startswith("unsloth/") or _cp_lower.startswith("nvidia/") - ): - trust_remote_code = True - logger.info( - "Auto-enabled trust_remote_code for Nemotron model: %s", - checkpoint_path, - ) - try: _send_response( resp_queue, diff --git a/studio/backend/core/inference/worker.py b/studio/backend/core/inference/worker.py index db504bac3a..85293162f5 100644 --- a/studio/backend/core/inference/worker.py +++ b/studio/backend/core/inference/worker.py @@ -34,50 +34,15 @@ from utils.hardware import apply_gpu_ids def _activate_transformers_version(model_name: str) -> None: - """Activate the correct transformers version BEFORE any ML imports. - - Uses get_transformers_tier() to decide between .venv_t5_550/ (5.5.0), - .venv_t5_530/ (5.3.0), or the default 4.57.x. - """ + """Activate the correct transformers version BEFORE any ML imports.""" # Ensure backend is on path for utils imports backend_path = str(Path(__file__).resolve().parent.parent.parent) if backend_path not in sys.path: sys.path.insert(0, backend_path) - from utils.transformers_version import ( - get_transformers_tier, - _resolve_base_model, - _ensure_venv_t5_530_exists, - _ensure_venv_t5_550_exists, - _VENV_T5_530_DIR, - _VENV_T5_550_DIR, - ) + from utils.transformers_version import activate_transformers_for_subprocess - resolved = _resolve_base_model(model_name) - tier = get_transformers_tier(resolved) - - if tier == "550": - if not _ensure_venv_t5_550_exists(): - raise RuntimeError( - f"Cannot activate transformers 5.5.0: .venv_t5_550 missing at {_VENV_T5_550_DIR}" - ) - if _VENV_T5_550_DIR not in sys.path: - sys.path.insert(0, _VENV_T5_550_DIR) - logger.info("Activated transformers 5.5.0 from %s", _VENV_T5_550_DIR) - _pp = os.environ.get("PYTHONPATH", "") - os.environ["PYTHONPATH"] = _VENV_T5_550_DIR + (os.pathsep + _pp if _pp else "") - elif tier == "530": - if not _ensure_venv_t5_530_exists(): - raise RuntimeError( - f"Cannot activate transformers 5.3.0: .venv_t5_530 missing at {_VENV_T5_530_DIR}" - ) - if _VENV_T5_530_DIR not in sys.path: - sys.path.insert(0, _VENV_T5_530_DIR) - logger.info("Activated transformers 5.3.0 from %s", _VENV_T5_530_DIR) - _pp = os.environ.get("PYTHONPATH", "") - os.environ["PYTHONPATH"] = _VENV_T5_530_DIR + (os.pathsep + _pp if _pp else "") - else: - logger.info("Using default transformers (4.57.x) for %s", model_name) + activate_transformers_for_subprocess(model_name) def _decode_image(image_base64: str): diff --git a/studio/backend/core/training/worker.py b/studio/backend/core/training/worker.py index edd88cc10f..6531c97102 100644 --- a/studio/backend/core/training/worker.py +++ b/studio/backend/core/training/worker.py @@ -407,50 +407,15 @@ def _ensure_flash_attn_for_long_context(event_queue: Any, max_seq_length: int) - def _activate_transformers_version(model_name: str) -> None: - """Activate the correct transformers version BEFORE any ML imports. - - Uses get_transformers_tier() to decide between .venv_t5_550/ (5.5.0), - .venv_t5_530/ (5.3.0), or the default 4.57.x. - """ + """Activate the correct transformers version BEFORE any ML imports.""" # Ensure backend is on path for utils imports backend_path = str(Path(__file__).resolve().parent.parent.parent) if backend_path not in sys.path: sys.path.insert(0, backend_path) - from utils.transformers_version import ( - get_transformers_tier, - _resolve_base_model, - _ensure_venv_t5_530_exists, - _ensure_venv_t5_550_exists, - _VENV_T5_530_DIR, - _VENV_T5_550_DIR, - ) + from utils.transformers_version import activate_transformers_for_subprocess - resolved = _resolve_base_model(model_name) - tier = get_transformers_tier(resolved) - - if tier == "550": - if not _ensure_venv_t5_550_exists(): - raise RuntimeError( - f"Cannot activate transformers 5.5.0: .venv_t5_550 missing at {_VENV_T5_550_DIR}" - ) - if _VENV_T5_550_DIR not in sys.path: - sys.path.insert(0, _VENV_T5_550_DIR) - logger.info("Activated transformers 5.5.0 from %s", _VENV_T5_550_DIR) - _pp = os.environ.get("PYTHONPATH", "") - os.environ["PYTHONPATH"] = _VENV_T5_550_DIR + (os.pathsep + _pp if _pp else "") - elif tier == "530": - if not _ensure_venv_t5_530_exists(): - raise RuntimeError( - f"Cannot activate transformers 5.3.0: .venv_t5_530 missing at {_VENV_T5_530_DIR}" - ) - if _VENV_T5_530_DIR not in sys.path: - sys.path.insert(0, _VENV_T5_530_DIR) - logger.info("Activated transformers 5.3.0 from %s", _VENV_T5_530_DIR) - _pp = os.environ.get("PYTHONPATH", "") - os.environ["PYTHONPATH"] = _VENV_T5_530_DIR + (os.pathsep + _pp if _pp else "") - else: - logger.info("Using default transformers (4.57.x) for %s", model_name) + activate_transformers_for_subprocess(model_name) def run_training_process( diff --git a/studio/backend/utils/transformers_version.py b/studio/backend/utils/transformers_version.py index 7e18086dca..cc6e154b30 100644 --- a/studio/backend/utils/transformers_version.py +++ b/studio/backend/utils/transformers_version.py @@ -95,6 +95,49 @@ _VENV_T5_550_DIR = str(Path.home() / ".unsloth" / "studio" / ".venv_t5_550") _VENV_T5_DIR = _VENV_T5_550_DIR +def activate_transformers_for_subprocess(model_name: str) -> None: + """Activate the correct transformers version in a subprocess worker. + + Call this BEFORE any ML imports. Resolves LoRA adapters to their base + model, determines the required tier, and prepends the appropriate + ``.venv_t5_*`` directory to ``sys.path``. Also propagates the path + via ``PYTHONPATH`` for child processes (e.g. GGUF converter). + + Used by training, inference, and export workers. + """ + resolved = _resolve_base_model(model_name) + tier = get_transformers_tier(resolved) + + if tier == "550": + if not _ensure_venv_t5_550_exists(): + raise RuntimeError( + f"Cannot activate transformers 5.5.0: " + f".venv_t5_550 missing at {_VENV_T5_550_DIR}" + ) + if _VENV_T5_550_DIR not in sys.path: + sys.path.insert(0, _VENV_T5_550_DIR) + logger.info("Activated transformers 5.5.0 from %s", _VENV_T5_550_DIR) + _pp = os.environ.get("PYTHONPATH", "") + os.environ["PYTHONPATH"] = ( + _VENV_T5_550_DIR + (os.pathsep + _pp if _pp else "") + ) + elif tier == "530": + if not _ensure_venv_t5_530_exists(): + raise RuntimeError( + f"Cannot activate transformers 5.3.0: " + f".venv_t5_530 missing at {_VENV_T5_530_DIR}" + ) + if _VENV_T5_530_DIR not in sys.path: + sys.path.insert(0, _VENV_T5_530_DIR) + logger.info("Activated transformers 5.3.0 from %s", _VENV_T5_530_DIR) + _pp = os.environ.get("PYTHONPATH", "") + os.environ["PYTHONPATH"] = ( + _VENV_T5_530_DIR + (os.pathsep + _pp if _pp else "") + ) + else: + logger.info("Using default transformers (4.57.x) for %s", model_name) + + def _resolve_base_model(model_name: str) -> str: """If *model_name* points to a LoRA adapter, return its base model. From bd4aa24bc69039775ab72ad2396868b52d3f6245 Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Mon, 6 Apr 2026 22:45:22 +0000 Subject: [PATCH 18/24] narrow Nemotron trust_remote_code to nemotron_h/nemotron-3-nano, add to export worker --- studio/backend/core/export/worker.py | 13 +++++++++++++ studio/backend/core/inference/worker.py | 6 ++++-- studio/backend/core/training/worker.py | 6 ++++-- 3 files changed, 21 insertions(+), 4 deletions(-) diff --git a/studio/backend/core/export/worker.py b/studio/backend/core/export/worker.py index 80b05aca79..f77b1966c4 100644 --- a/studio/backend/core/export/worker.py +++ b/studio/backend/core/export/worker.py @@ -206,6 +206,19 @@ def _handle_load(backend, cmd: dict, resp_queue: Any) -> None: load_in_4bit = cmd.get("load_in_4bit", True) trust_remote_code = cmd.get("trust_remote_code", False) + # Auto-enable trust_remote_code for NemotronH/Nano models. + if not trust_remote_code: + _NEMOTRON_TRUST_SUBSTRINGS = ("nemotron_h", "nemotron-h", "nemotron-3-nano") + _cp_lower = checkpoint_path.lower() + if any(sub in _cp_lower for sub in _NEMOTRON_TRUST_SUBSTRINGS) and ( + _cp_lower.startswith("unsloth/") or _cp_lower.startswith("nvidia/") + ): + trust_remote_code = True + logger.info( + "Auto-enabled trust_remote_code for Nemotron model: %s", + checkpoint_path, + ) + try: _send_response( resp_queue, diff --git a/studio/backend/core/inference/worker.py b/studio/backend/core/inference/worker.py index 85293162f5..fbcce276ba 100644 --- a/studio/backend/core/inference/worker.py +++ b/studio/backend/core/inference/worker.py @@ -287,14 +287,16 @@ def _handle_load(backend, config: dict, resp_queue: Any) -> None: except Exception as e: logger.warning("Could not read adapter_config.json: %s", e) - # Auto-enable trust_remote_code for Nemotron models only. + # Auto-enable trust_remote_code for NemotronH/Nano models only. # NemotronH has config parsing bugs requiring trust_remote_code=True. # Other transformers 5.x models are native and do NOT need it. + # NOTE: Must NOT match Llama-Nemotron (standard Llama architecture). + _NEMOTRON_TRUST_SUBSTRINGS = ("nemotron_h", "nemotron-h", "nemotron-3-nano") trust_remote_code = config.get("trust_remote_code", False) if not trust_remote_code: model_name = config["model_name"] _mn_lower = model_name.lower() - if "nemotron" in _mn_lower and ( + if any(sub in _mn_lower for sub in _NEMOTRON_TRUST_SUBSTRINGS) and ( _mn_lower.startswith("unsloth/") or _mn_lower.startswith("nvidia/") ): trust_remote_code = True diff --git a/studio/backend/core/training/worker.py b/studio/backend/core/training/worker.py index 6531c97102..cca1c9b632 100644 --- a/studio/backend/core/training/worker.py +++ b/studio/backend/core/training/worker.py @@ -465,14 +465,16 @@ def run_training_process( ) return - # ── 1a. Auto-enable trust_remote_code for Nemotron models ── + # ── 1a. Auto-enable trust_remote_code for NemotronH/Nano models ── # NemotronH has config parsing bugs in transformers that require # trust_remote_code=True as a workaround. Other transformers 5.x models # (Qwen3.5, Gemma 4, etc.) are native and do NOT need it — enabling it # bypasses the compiler (disabling fused CE). + # NOTE: Must NOT match Llama-Nemotron (standard Llama architecture). + _NEMOTRON_TRUST_SUBSTRINGS = ("nemotron_h", "nemotron-h", "nemotron-3-nano") _lowered = model_name.lower() if ( - "nemotron" in _lowered + any(sub in _lowered for sub in _NEMOTRON_TRUST_SUBSTRINGS) and (_lowered.startswith("unsloth/") or _lowered.startswith("nvidia/")) and not config.get("trust_remote_code", False) ): From c3c03388ea7a05a68a8e3bd28e31df3de836827e Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Mon, 6 Apr 2026 22:46:14 +0000 Subject: [PATCH 19/24] clean venv_t5 dirs before re-install in setup.sh, clarify version alias comment --- studio/backend/utils/transformers_version.py | 3 ++- studio/setup.sh | 2 ++ 2 files changed, 4 insertions(+), 1 deletion(-) diff --git a/studio/backend/utils/transformers_version.py b/studio/backend/utils/transformers_version.py index cc6e154b30..b17d8cf3c6 100644 --- a/studio/backend/utils/transformers_version.py +++ b/studio/backend/utils/transformers_version.py @@ -85,7 +85,8 @@ _config_needs_550_cache: dict[str, bool] = {} TRANSFORMERS_550_VERSION = "5.5.0" TRANSFORMERS_530_VERSION = "5.3.0" TRANSFORMERS_DEFAULT_VERSION = "4.57.6" -# Backwards-compat alias used by other modules +# Backwards-compat alias — points to 5.5.0 (the highest 5.x tier). +# Consumers should prefer TRANSFORMERS_530_VERSION / TRANSFORMERS_550_VERSION. TRANSFORMERS_5_VERSION = TRANSFORMERS_550_VERSION # Pre-installed directories — created by setup.sh / setup.ps1 diff --git a/studio/setup.sh b/studio/setup.sh index 0b9ca8383b..4e6153d0ae 100755 --- a/studio/setup.sh +++ b/studio/setup.sh @@ -551,6 +551,7 @@ if [ "$_SKIP_PYTHON_DEPS" = false ]; then # Clean up legacy single .venv_t5 directory [ -d "$STUDIO_HOME/.venv_t5" ] && rm -rf "$STUDIO_HOME/.venv_t5" + [ -d "$VENV_T5_530_DIR" ] && rm -rf "$VENV_T5_530_DIR" mkdir -p "$VENV_T5_530_DIR" run_quiet "install transformers 5.3.0" fast_install --target "$VENV_T5_530_DIR" --no-deps "transformers==5.3.0" run_quiet "install huggingface_hub for t5_530" fast_install --target "$VENV_T5_530_DIR" --no-deps "huggingface_hub==1.8.0" @@ -558,6 +559,7 @@ if [ "$_SKIP_PYTHON_DEPS" = false ]; then run_quiet "install tiktoken for t5_530" fast_install --target "$VENV_T5_530_DIR" "tiktoken" step "transformers" "5.3.0 pre-installed" + [ -d "$VENV_T5_550_DIR" ] && rm -rf "$VENV_T5_550_DIR" mkdir -p "$VENV_T5_550_DIR" run_quiet "install transformers 5.5.0" fast_install --target "$VENV_T5_550_DIR" --no-deps "transformers==5.5.0" run_quiet "install huggingface_hub for t5_550" fast_install --target "$VENV_T5_550_DIR" --no-deps "huggingface_hub==1.8.0" From fe842482a2992fe6914b12a3ecd8ebc9fddf9637 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 6 Apr 2026 22:46:58 +0000 Subject: [PATCH 20/24] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- studio/backend/utils/transformers_version.py | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) diff --git a/studio/backend/utils/transformers_version.py b/studio/backend/utils/transformers_version.py index b17d8cf3c6..36c3a4c22d 100644 --- a/studio/backend/utils/transformers_version.py +++ b/studio/backend/utils/transformers_version.py @@ -119,9 +119,7 @@ def activate_transformers_for_subprocess(model_name: str) -> None: sys.path.insert(0, _VENV_T5_550_DIR) logger.info("Activated transformers 5.5.0 from %s", _VENV_T5_550_DIR) _pp = os.environ.get("PYTHONPATH", "") - os.environ["PYTHONPATH"] = ( - _VENV_T5_550_DIR + (os.pathsep + _pp if _pp else "") - ) + os.environ["PYTHONPATH"] = _VENV_T5_550_DIR + (os.pathsep + _pp if _pp else "") elif tier == "530": if not _ensure_venv_t5_530_exists(): raise RuntimeError( @@ -132,9 +130,7 @@ def activate_transformers_for_subprocess(model_name: str) -> None: sys.path.insert(0, _VENV_T5_530_DIR) logger.info("Activated transformers 5.3.0 from %s", _VENV_T5_530_DIR) _pp = os.environ.get("PYTHONPATH", "") - os.environ["PYTHONPATH"] = ( - _VENV_T5_530_DIR + (os.pathsep + _pp if _pp else "") - ) + os.environ["PYTHONPATH"] = _VENV_T5_530_DIR + (os.pathsep + _pp if _pp else "") else: logger.info("Using default transformers (4.57.x) for %s", model_name) From c379471e45f367852fccf85f44a8a7d9253d34ee Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Tue, 7 Apr 2026 07:24:47 +0000 Subject: [PATCH 21/24] update --- studio/setup.sh | 28 +++++++++++++++++++++------- 1 file changed, 21 insertions(+), 7 deletions(-) diff --git a/studio/setup.sh b/studio/setup.sh index 4e6153d0ae..420076ff3a 100755 --- a/studio/setup.sh +++ b/studio/setup.sh @@ -490,15 +490,29 @@ if [ "$_DOCKER_NO_VENV" = true ]; then # install_python_stack.py has steps 1-5 commented out for this branch. python "$SCRIPT_DIR/install_python_stack.py" - # Pre-install transformers 5.x into .venv_t5 + # Pre-install transformers 5.x into .venv_t5_530/ and .venv_t5_550/ echo "" echo " Pre-installing transformers 5.x for newer model support..." - mkdir -p "$VENV_T5_DIR" - pip install --target "$VENV_T5_DIR" --no-deps "transformers==5.3.0" 2>/dev/null - pip install --target "$VENV_T5_DIR" --no-deps "huggingface_hub==1.7.1" 2>/dev/null - pip install --target "$VENV_T5_DIR" --no-deps "hf_xet==1.4.2" 2>/dev/null - pip install --target "$VENV_T5_DIR" "tiktoken" 2>/dev/null - echo "✅ Transformers 5.x pre-installed to $VENV_T5_DIR/" + + # Clean up legacy single .venv_t5 directory + [ -d "$STUDIO_HOME/.venv_t5" ] && rm -rf "$STUDIO_HOME/.venv_t5" + + [ -d "$VENV_T5_530_DIR" ] && rm -rf "$VENV_T5_530_DIR" + mkdir -p "$VENV_T5_530_DIR" + pip install --target "$VENV_T5_530_DIR" --no-deps "transformers==5.3.0" 2>/dev/null + pip install --target "$VENV_T5_530_DIR" --no-deps "huggingface_hub==1.8.0" 2>/dev/null + pip install --target "$VENV_T5_530_DIR" --no-deps "hf_xet==1.4.2" 2>/dev/null + pip install --target "$VENV_T5_530_DIR" "tiktoken" 2>/dev/null + + [ -d "$VENV_T5_550_DIR" ] && rm -rf "$VENV_T5_550_DIR" + mkdir -p "$VENV_T5_550_DIR" + pip install --target "$VENV_T5_550_DIR" --no-deps "transformers==5.5.0" 2>/dev/null + pip install --target "$VENV_T5_550_DIR" --no-deps "huggingface_hub==1.8.0" 2>/dev/null + pip install --target "$VENV_T5_550_DIR" --no-deps "hf_xet==1.4.2" 2>/dev/null + pip install --target "$VENV_T5_550_DIR" "tiktoken" 2>/dev/null + + echo "✅ Transformers 5.3.0 pre-installed to $VENV_T5_530_DIR/" + echo "✅ Transformers 5.5.0 pre-installed to $VENV_T5_550_DIR/" echo "" echo "╔══════════════════════════════════════╗" From fce1a1e8453745f6548b9c68eee69ee8180690cc Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Sun, 5 Apr 2026 05:22:43 +0000 Subject: [PATCH 22/24] fix: derive HF_HUB_CACHE from HF_HOME when set Previously HF_HUB_CACHE always defaulted to ~/.cache/huggingface/hub even when HF_HOME was explicitly set (e.g. in Docker). This caused models to download to the wrong location instead of the configured HF_HOME path. --- studio/backend/utils/paths/storage_roots.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/studio/backend/utils/paths/storage_roots.py b/studio/backend/utils/paths/storage_roots.py index b52609b06b..396c440ac4 100644 --- a/studio/backend/utils/paths/storage_roots.py +++ b/studio/backend/utils/paths/storage_roots.py @@ -193,10 +193,11 @@ def _setup_cache_env() -> None: os.environ.get("XDG_CACHE_HOME", Path.home() / ".cache") ).expanduser() hf_default = xdg_cache / "huggingface" + hf_home = Path(os.environ.get("HF_HOME", str(hf_default))) defaults: dict[str, str] = { "HF_HOME": str(hf_default), - "HF_HUB_CACHE": str(hf_default / "hub"), - "HF_XET_CACHE": str(hf_default / "xet"), + "HF_HUB_CACHE": str(hf_home / "hub"), + "HF_XET_CACHE": str(hf_home / "xet"), "UV_CACHE_DIR": str(root / "uv"), "VLLM_CACHE_ROOT": str(root / "vllm"), } From c3cec00ca817c77b6593af03321c533ae51e1ad7 Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Thu, 16 Apr 2026 00:48:14 +0400 Subject: [PATCH 23/24] spark studio v0.13.6 2026.4.5 --- .worktreeinclude | 1 + 1 file changed, 1 insertion(+) create mode 100644 .worktreeinclude diff --git a/.worktreeinclude b/.worktreeinclude new file mode 100644 index 0000000000..ceb2b988dc --- /dev/null +++ b/.worktreeinclude @@ -0,0 +1 @@ +CLAUDE.md From 8a531e3290ffa40b8ac910af942659be99a37352 Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Thu, 16 Apr 2026 01:21:18 +0400 Subject: [PATCH 24/24] removed flash attention --- studio/backend/core/training/worker.py | 8 ++++---- studio/install_python_stack.py | 6 +++--- 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/studio/backend/core/training/worker.py b/studio/backend/core/training/worker.py index cca1c9b632..19b9990ce9 100644 --- a/studio/backend/core/training/worker.py +++ b/studio/backend/core/training/worker.py @@ -488,10 +488,10 @@ def run_training_process( try: _ensure_causal_conv1d_fast_path(event_queue, model_name) _ensure_mamba_ssm(event_queue, model_name) - _ensure_flash_attn_for_long_context( - event_queue, - int(config.get("max_seq_length", 2048)), - ) + #_ensure_flash_attn_for_long_context( + # event_queue, + # int(config.get("max_seq_length", 2048)), + #) except Exception as exc: event_queue.put( { diff --git a/studio/install_python_stack.py b/studio/install_python_stack.py index 1ef626ce39..bacf8bc7ed 100644 --- a/studio/install_python_stack.py +++ b/studio/install_python_stack.py @@ -989,9 +989,9 @@ def install_python_stack() -> int: # constrain = False, # ) - if not IS_WINDOWS and not IS_MACOS and not NO_TORCH: - _progress("flash-attn") - _ensure_flash_attn() + #if not IS_WINDOWS and not IS_MACOS and not NO_TORCH: + # _progress("flash-attn") + # _ensure_flash_attn() # # 6. Patch: override llama_cpp.py with fix from unsloth-zoo feature/llama-cpp-windows-support branch # patch_package_file(