mlcommons / mlcommons/modelbench

Add support for HF serverless, and specifially Gemma-3-27B-it

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Dominant language
Python
Stars
134
Forks
36
Avg merge
1d 11h
Merged PRs (30d)
17

Description

This issue has no description.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by locating the existing model-provider integrations and the benchmark entry points in the ModelBench repository. Trace how a model is configured and invoked, then determine what support for Hugging Face Serverless and Gemma-3-27B-it requires. Done means both the serverless service and the named model can run through the benchmark workflow.

Written by the indexing model from the issue text.

Assessment

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

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