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Signed-off-by: Zhang, Weiwei1 <weiwei1.zhang@intel.com>
@wenhuach21 wenhuach21 changed the title enable dynamic quantization config saving enable regex quantization config saving Sep 16, 2025
@wenhuach21 wenhuach21 changed the title enable regex quantization config saving enable regex quantization config saving for mixed bits Sep 16, 2025
WeiweiZhang1 and others added 2 commits September 16, 2025 16:02
Signed-off-by: Zhang, Weiwei1 <weiwei1.zhang@intel.com>
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wenhuach21 commented Sep 16, 2025

TODO:
1 Supported the inference for AutoRound format in Transformers
2 Validated the inference for AutoRound format in vLLMs/Sglang
3 ADD UTs

@WeiweiZhang1 WeiweiZhang1 removed the WIP label Oct 16, 2025
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Have you validated the GPTQ format? Even without regex in the layer_config , the configuration should still be set under the dynamic key in some way.

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Have you validated the GPTQ format? Even without regex in the layer_config , the configuration should still be set under the dynamic key in some way.

sure, also added UT for auto_gptq format infer & convert to autoround format infer

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could you also have a check whether this issue have been resolved by this pr
#902

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Qwen3-VL-30B-A3B-Instruc or smaller model is ok. And transformers is enough, no need to verify on vllm ,as vllm should not be able to support our converted model.

@WeiweiZhang1 WeiweiZhang1 merged commit 873114a into main Oct 23, 2025
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@WeiweiZhang1 WeiweiZhang1 deleted the enable_dynamic_quantization_config_saving branch October 23, 2025 01:45
chensuyue added a commit that referenced this pull request Nov 11, 2025
* Fix rtn tuning_device issue (#893)

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* fix vlm gguf ut (#895)

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* update alg_ext.abi3.so with python compatible version (#894)

* move ste from quant to round for nvfp4 (#889)

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* Add GPT-OSS quant support (#887)

* better help printing information (#883)

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* Update auto_round/compressors/base.py

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* fix nvfp act quantization bug (#891)

* fix nvfp act quantization bug

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* support automatic mixed bits assignment (#851)

* try to fix gguf issue (#886)

* remove numba from requirments (#905)

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* Extend mxfp loading dtypes (#907)

* block dataset logger info (#908)

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* fix torch compile issue in AutoScheme (#909)

* Revert "Extend mxfp loading dtypes (#907)" (#915)

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* support disable_opt_rtn in auto-scheme (#913)

* fix llama 4 ut (#896)

* fix ut of llama 4

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* Loosen the packing restrictions for mxfp&nvfp (#911)

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* Fix act config exporting for mixed schemes (#903)

* fp8 exporting bugfix

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* optimize rtn for int woq (#924)

* fix bug of gguf and support for LiquidAI/LFM2-1.2B (#927)

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* remove numpy<2.0 limitation (#921)

* enable regex quantization config saving for mixed bits (#825)

* enable dynamic quantization config saving

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* Fix Flux tuning issue (#936)

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* gguf support for inclusionAI/Ling-flash-2.0 (#940)

* remove low_cpu_mem (#934)

* Add compatibility test (#918)

* Add commit hash to version (#941)

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* gguf weight type align with original, output.weight, token_embed (#900)

* support attention mask in user's dataset (#930)

* Add diffusion README (#923)

* update readme (#949)

* refactor utils file (#943)

* refact utils

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* update gguf and support for CompressedLinear (#950)

* Reduce AutoSchem VRAM usage by up to 10X (#944)

* add self attribution and fix avg_bits error (#956)

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* add logo (#960)

* refine AutoScheme readme/code (#958)

* update readme (#962)

* fix critic disable_opt_rtn regression (#963)

* [1/N] Initial vllm-ext evaluation support (MXFP4 MOE) (#935)

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* fix bug of imatrix contains 0 (#955)

* fix rtn bug (#966)

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* clean code (#968)

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* fix cuda CI backend issue, fixtypo (#974)

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* cli support for positional arguments model (#979)

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* update bits (#986)

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* add support for Magistral-Small (#980)

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