Two fixes for accurate GGUF OOM detection:
1. /api/system now uses nvidia-smi to enumerate all physical GPUs
instead of torch.cuda which only sees CUDA_VISIBLE_DEVICES. This
matches llama-server which can use all GPUs regardless of the env
var. Falls back to torch-based detection if nvidia-smi unavailable.
2. Frontend GGUF OOM check now uses 70% of total GPU memory as the
budget, matching the PR's _select_gpus logic (30% reserved for KV
cache and compute buffers). Previously used checkVramFit's 100%
threshold which was too generous.
* fix: quotation marks
* diceware passphrase generation
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: Roland Tannous <rolandtannous@gravityq.ai>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
The studio was disabling flex attention entirely on Blackwell+ GPUs
(sm_120 and above) by setting UNSLOTH_ENABLE_FLEX_ATTENTION=0 at
startup. This was a workaround for the flex_attention backward kernel
exceeding shared memory limits on these GPUs.
The root cause is now fixed in unsloth-zoo (PR #542) which patches the
backward kernel config selection to generate safe fallback configs that
fit within the GPU's shared memory limit. With that fix, flex attention
works correctly on Blackwell GPUs and provides a ~1.3x speedup over
the SDPA fallback.
All version switching now uses .venv_t5/ (pre-installed by setup.sh).
The old .venv_overlay/ with runtime pip installs is removed.
ensure_transformers_version() (used only by export) now does a
lightweight sys.path swap instead of pip installing at runtime.
