feat: add support for FP8 model loading and ragged-tile dequantization fallback - #2158
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xin3he wants to merge 4 commits into
Open
feat: add support for FP8 model loading and ragged-tile dequantization fallback#2158xin3he wants to merge 4 commits into
xin3he wants to merge 4 commits into
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Pull request overview
This PR adds first-class support for loading FP8-quantized checkpoints (specifically DeepSeek v3.2) by detecting FP8 quantization from the model config and enabling dequantize-on-load, plus a fallback patch to handle “ragged tile” FP8 scale grids during dequantization.
Changes:
- Add FP8 model detection via config inspection and automatically pass
FineGrainedFP8Config(dequantize=True)during model load (transformers ≥ 4.56.0). - Patch transformers’ FP8 dequantization to fall back to AutoRound’s dequantizer when scale-grid divisibility checks fail due to over-provisioned grids.
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 4 comments.
| File | Description |
|---|---|
| auto_round/utils/model.py | Detect FP8 checkpoints (DeepSeek v3.2) and adjust from_pretrained kwargs to enable dequantize-on-load. |
| auto_round/modeling/fp8_quant.py | Add a patch for FP8 ragged-tile dequantization mismatches by falling back to AutoRound’s robust dequantizer. |
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Collaborator
|
/azp run Unit-Test-CUDA-AutoRound |
|
Azure Pipelines successfully started running 1 pipeline(s). |
…n fallback Signed-off-by: Xin He <xin3.he@intel.com>
for more information, see https://pre-commit.ci
Signed-off-by: Xin He <xin3.he@intel.com>
for more information, see https://pre-commit.ci
Collaborator
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/azp run Unit-Test-CUDA-AutoRound |
|
Azure Pipelines successfully started running 1 pipeline(s). |
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Description
support deepseek v3.2
Type of Change
Bug fix
Related Issues
Fixes or relates to #
Checklist Before Submitting
/azp run Unit-Test-CUDA-AutoRound.