[Bugfix] Fix CI bitsandbytes failure

[jeejeelee]

Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

Purpose

FIX #19964
This OOM issue is probably caused by the recent implementation of V1 support for the embedding model

Test Plan

Test Result

The quantization/test_bitsandbytes.py::test_4bit_bnb_embedding_model[half-intfloat/e5-mistral-7b-instruct-quantize embedding model inflight] should pass on CI

(Optional) Documentation Update

[gemini-code-assist]

Summary of Changes

Hello @jeejeelee, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request addresses a recurring Out-Of-Memory (OOM) issue encountered in CI tests, specifically affecting bitsandbytes quantization tests for embedding models. My change involves adjusting the GPU memory allocation for a particular test to prevent these failures, aiming to improve the overall stability of our continuous integration pipeline.

Highlights

• CI Stability / OOM Fix: I've updated the test_4bit_bnb_embedding_model in tests/quantization/test_bitsandbytes.py to explicitly set gpu_memory_utilization to 0.5 when initializing the vllm_runner. This change is intended to mitigate Out-Of-Memory (OOM) errors observed in CI, particularly for tests involving bitsandbytes quantization with embedding models.

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[github-actions]

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[gemini-code-assist]

Code Review

The pull request adds gpu_memory_utilization=0.5 to the vllm_runner in the test_4bit_bnb_embedding_model test case to fix a CI failure related to OOM issues with embedding models when using bitsandbytes quantization. This change aims to reduce GPU memory usage during the test.

[mgoin]

Thank you!