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[WIP] Include GPT Fast in torch.compile nightly benchmark workflow #2857
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lxning
reviewed
Dec 20, 2023
| gpt_fast: | ||
| 7b_int4: | ||
| benchmark_engine: "ab" | ||
| url: https://torchserve.pytorch.org/mar_files/gpt_fast_7b_int4.mar |
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please clearly specify the model in the name. eg. Llama-2-7b-hf
| backend_profiling: False | ||
| exec_env: "local" | ||
| processors: | ||
| - "cpu" |
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|
@namannandan @lxning What is the work remaining for this PR? |
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Description
Please read our CONTRIBUTING.md prior to creating your first pull request.
The objective of this PR is to include the GPT Fast model with weights corresponding to Llama 7B with int4 quantization.
Steps to download Llama 7B weights in the benchmark host:
Ran a temporary workflow to download weights with the HUGGING_FACE_HUB_TOKEN in the commit 1e6088e
Results of successful run: https://github.com/pytorch/serve/actions/runs/7271384883/job/19811851851?pr=2857
Testing:
Ran benchmark workflow in the commit 31936c9
Results of the successful run: https://github.com/pytorch/serve/actions/runs/7272224847/job/19813999840?pr=2857
Benchmark report file: report.md
Updates in benchmark-ab.py script:
Also updated the
benchmark-ab.pyscript to include-lin theabcommands to allow variable response lengths without counting them as errors (https://httpd.apache.org/docs/2.4/programs/ab.html).