Gahow Wang
445e491123
third_party/vllm/ now tracked in git for direct patch management.
Based on vLLM v0.18.1 release with one patch applied:
vllm/v1/core/sched/scheduler.py:
Replace fatal assert with graceful skip when KV transfer callback
arrives for an already-aborted request during PD disaggregated serving.
Future vLLM modifications should be made directly in third_party/vllm/
and committed normally. The patches/ directory is kept as documentation
of what changed from upstream.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
GSM8K Accuracy Evaluation
This directory contains a replacement for the lm-eval-harness GSM8K evaluation, using an isolated GSM8K script and vLLM server for better performance and control.
Usage
Run tests with pytest (like buildkite)
pytest -s -v tests/evals/gsm8k/test_gsm8k_correctness.py \
--config-list-file=configs/models-small.txt
Run standalone evaluation script
# Start vLLM server first
vllm serve Qwen/Qwen2.5-1.5B-Instruct --port 8000
# Run evaluation
python tests/evals/gsm8k/gsm8k_eval.py --port 8000
Configuration Format
Model configs in configs/ directory use this YAML format:
model_name: "Qwen/Qwen2.5-1.5B-Instruct"
accuracy_threshold: 0.54 # Minimum expected accuracy
num_questions: 1319 # Number of questions (default: full test set)
num_fewshot: 5 # Few-shot examples from train set
server_args: "--max-model-len 4096 --tensor-parallel-size 2" # Server arguments
env: # Environment variables (optional)
VLLM_USE_FLASHINFER_MOE_FP4: "1"
The server_args field accepts any arguments that can be passed to vllm serve.
The env field accepts a dictionary of environment variables to set for the server process.