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Merge pull request #1 from neuralmagic/begin
Create repo and add initial files
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README.md

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# model-validation-configs
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# model-validation-configs
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This repository contains configurations for model validation.
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The `accuracy` folder contains YAML files for each model that configures information needed for the model to be validated through the [llm-eval-test](https://github.com/openshift-psap/llm-eval-test). There are 4 config files for each model:
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* server.yml: contains settings to start a vllm server with the model
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* client.yml: contains settings for the llm-eval-test harness for the model
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* accuracy.yml: contains evaluation tasks and accuracy expectations for the model
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* storage.yml: specifies where mode and dataset is located
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# accuracy configs for https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct
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tasks:
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- name: "leaderboard_bbh"
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metrics:
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- name: "acc_norm,none"
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value: 0.50946
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- name: "leaderboard_gpqa"
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metrics:
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- name: "acc_norm,none"
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value: 0.29698
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- name: "leaderboard_ifeval"
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metrics:
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- name: "inst_level_loose_acc,none"
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value: 0.85851
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- name: "inst_level_strict_acc,none"
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value: 0.82374
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- name: "prompt_level_loose_acc,none"
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value: 0.79667
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- name: "prompt_level_strict_acc,none"
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value: 0.74861
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- name: "leaderboard_math_hard"
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metrics:
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- name: "exact_match,none"
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value: 0.19864
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- name: "leaderboard_musr"
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metrics:
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- name: "acc_norm,none"
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value: 0.38359
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# llm-eval-test configs for https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct
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model: "vllm"
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model_args:
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pretrained: "meta-llama/Meta-Llama-3.1-8B-Instruct"
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num_fewshot:
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apply_chat_template: true
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fewshot_as_multiturn: true
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add_bos_token: false
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# server configs for https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct
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model: "meta-llama/Meta-Llama-3.1-8B-Instruct"
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trust_remote_code: true
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enable_chunked_prefill: true
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tensor_parallel_size:
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max_model_len: 4096
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# storage configs for https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct
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model: hf
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data: hf

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