intel / intel/auto-round

[Feature]: support and eval H-Scale: Hessian-Guided Scale Refinement for NVFP4 Sub-Byte LLM Inference

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#2,262 0 comments 0 reactions 0 assignees View on GitHub
enhancement
Dominant language
Python
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Forks
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Avg merge
1d 18h
Merged PRs (30d)
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Description

### Feature Description

Though I think iMatrix has already done a large part of the work for Hessian part, let's evaluate it when we have some bandwidth.

### Motivation and Use Case

~

### Alternatives Considered

~

### Definition of Done

_No response_

### Additional Context

_No response_

Contributor guide

Open the contributing guide

Research direction

No files, tests, entry points, or acceptance criteria are named. Start by locating the existing iMatrix Hessian-related implementation and the NVFP4 quantization and inference entry points, then determine how H-Scale should be evaluated and what results would constitute completion.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Active
Clarity
Needs clarification
Newbie friendliness
25/100

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