forked from phoenix-oss/llama-stack-mirror
f369871083
# What does this PR do? In this PR, we added a new eval open benchmark IfEval based on paper https://arxiv.org/abs/2311.07911 to measure the model capability of instruction following. ## Test Plan spin up a llama stack server with open-benchmark template run `llama-stack-client --endpoint xxx eval run-benchmark "meta-reference-ifeval" --model-id "meta-llama/Llama-3.3-70B-Instruct" --output-dir "/home/markchen1015/" --num-examples 20` on client side and get the eval aggregate results |
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| .. | ||
| __init__.py | ||
| agents.py | ||
| datasetio.py | ||
| eval.py | ||
| inference.py | ||
| post_training.py | ||
| safety.py | ||
| scoring.py | ||
| telemetry.py | ||
| tool_runtime.py | ||
| vector_io.py | ||