support AR format FP8 in vLLM#1798
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Pull request overview
This PR aims to enable exporting block-wise FP8 quantization using the auto_round / auto_round:fp8 format (targeting vLLM compatibility), rather than forcing users to export with the standalone fp8 format.
Changes:
- Removes the format-compatibility rewrite that previously replaced
auto_roundwithfp8for block-wise FP8 configs. - Updates FP8 export to always emit
weight_block_sizefor tuplegroup_size, and additionally emitsmodules_to_not_convertalongsideignored_layersfor layers kept in high precision.
This was referenced May 11, 2026
wenhuach21
reviewed
May 12, 2026
| formats = tmp_format_name.split(",") | ||
| if isinstance(ar.group_size, tuple) and any(["auto_round" in f.lower() for f in formats]): | ||
| logger.warning( | ||
| "`auto_round` format can't be used for deploying block-wise fp8 quantization now, use `fp8` instead." |
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Please keep the warning and change it to: auto_round:fp8 format only supports vLLM inference for now. We recommend using the FP8 format via --format fp8 instead .
wenhuach21
approved these changes
May 12, 2026
wenhuach21
reviewed
May 12, 2026
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| if isinstance(ar.group_size, tuple) and any(["auto_round" in f.lower() for f in formats]): | ||
| logger.warning( | ||
| "auto_round:fp8 format only supports vLLM inference for now. We recommend using the FP8 format via --format fp8 instead." |
yiliu30
approved these changes
May 13, 2026
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Please add some UTs; others LGTM.
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Related Issues
#1536
Type of Change
New feature
Test
Output Model:
