- Introduced `ViewportControls` for zoom, fit view, and interactive toggle in canvas lab.
- Extracted and reused `CANVAS_FLOATING_ICON_BUTTON_CLASS` for consistent button styling.
- Updated API base paths and server proxy settings.
- Enabled dynamic interaction states for nodes and connections in canvas lab.
* convert print to logger
* Print but cleaner
* Hide model on multiple devices
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix typo
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix typo transfomers -> transformers, revert MoE message change
* Update MoE detection message to show num_experts and target_modules
* Fix llama-cli path in save info message
* target_parameters warning for moe
* fix should_convert_module for llm_int8_skip_modules
* fix should_convert_module for llm_int8_skip_modules
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Logging filters
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* negation
* remove should_convert_module patch
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Hanchen <danielhanchen@users.noreply.github.com>
* Fix warmup_ratio deprecation warning for transformers >= 5.0
In transformers 5.0, warmup_ratio is deprecated in favor of
warmup_steps which now accepts float values (< 1 = ratio,
>= 1 = absolute steps).
The compiler now conditionally sets warmup_steps=0.1 on
transformers >= 5.0 (same semantics as warmup_ratio=0.1) and
keeps warmup_ratio=0.1 on older versions where warmup_steps
only accepts int.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: Daniel Hanchen <danielhanchen@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Inject token_type_ids for Gemma3 multimodal training on transformers 5.x
In transformers 5.x, create_causal_mask_mapping() raises ValueError when
is_training=True and token_type_ids is None. When doing text-only SFT on
Gemma3 4B (a multimodal model), the dataset_utils detection for
_needs_token_type_ids can miss because:
- The model is wrapped in PeftModel, so type(model).__module__ points to
peft.peft_model instead of transformers
- The processing_class is a tokenizer (not Gemma3Processor), so the
fallback MRO check resolves to a module without create_causal_mask_mapping
This adds a fallback in _unsloth_pre_compute_loss that injects
token_type_ids=zeros when:
1. token_type_ids is not already in inputs
2. The inner model config has model_type "gemma3"
3. The model's module has create_causal_mask_mapping (transformers 5.x)
4. The model is in training mode
On transformers 4.x, create_causal_mask_mapping does not exist so this
check is inert.
Depends on: unslothai/unsloth-zoo#488
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: Daniel Hanchen <danielhanchen@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* FP8: Load model on-the-fly in vLLM
**Summary:** Existing support for `load_in_fp8=True` performs
an offline quantization when loading the initial model.
This is no longer necessary as of vllm==0.12.0 (after
https://github.com/vllm-project/vllm/pull/23014), where we
can quantize the model on-the-fly when we load it:
```
llm = LLM(
...
hf_overrides={
"quantization_config_dict_str": json.dumps(torchao_config),
},
)
```
**Note:** Needs https://github.com/unslothai/unsloth-zoo/pull/380
**Test Plan:**
https://gist.github.com/andrewor14/5b85119fae46845d07b608d420907423
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix on-the-fly FP8: always check mapper first, fallback to on-the-fly
The original implementation bypasses the FP8 mapper entirely for
vllm >= 0.12.0, meaning models like Llama-3.2-1B-Instruct and Qwen3-8B
that have pre-quantized FP8-Block/FP8 checkpoints would never use them.
This fixes the priority order:
1. Mapper has a pre-quantized model -> use it (always)
2. Mapper has no match + vllm >= 0.12.0 -> on-the-fly FP8 via torchao
3. Mapper has no match + vllm < 0.12.0 -> offline quantization
Changes:
- loader_utils.py: Move vllm >= 0.12.0 check after mapper lookups
- loader.py: Set load_in_fp8=False when mapper resolves to a
pre-quantized model to prevent double quantization
Tested on B200 with Llama-3.2-1B-Instruct and Qwen3-8B. Corrected code
produces results matching baseline (pre-quantized path preserved).
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Hanchen <danielhanchen@users.noreply.github.com>
* convert print to logger
* Print but cleaner
* Hide model on multiple devices
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix typo
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix typo transfomers -> transformers, revert MoE message change
* Update MoE detection message to show num_experts and target_modules
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Hanchen <danielhanchen@users.noreply.github.com>
* Fix#3397: Prevent trainer tokenization hang with safe num_proc
* Fix#3397: Add missing import sys for Windows-safe tokenization
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Consolidate with existing num_proc guard in dataset_utils.py
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Hanchen <danielhanchen@users.noreply.github.com>
* Fix EmbeddingGemma float16 NaN by adding gemma3_text to FORCE_FLOAT32 and SDPA lists
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: Daniel Hanchen <danielhanchen@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Inject model reference for dynamic token_type_ids detection in SFTTrainer
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: Daniel Hanchen <danielhanchen@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Suppress vLLM v1 executor sleep/wake log messages
Add HideLoggingMessage filters for vllm.v1.executor.abstract logger to
suppress repetitive sleep/wake INFO and WARNING messages that spam training
output when UNSLOTH_VLLM_STANDBY is enabled. The existing filter at line 275
handles the legacy vllm.executor.executor_base path; this adds coverage for
the v1 engine path used by vllm 0.11+.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: Daniel Hanchen <danielhanchen@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
- Moved `AvailableVariables` to shared directory.
- Updated dialogs to use shared `AvailableVariables` component.
- Enhanced inline expressions and processors dialog with better variable display.
