wehub-resource-sync
65 lines
1.8 KiB
Python
65 lines
1.8 KiB
Python
import os
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os.environ['CUDA_VISIBLE_DEVICES'] = '0'
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os.environ['ASCEND_RT_VISIBLE_DEVICES'] = '0'
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infer_backend = 'transformers'
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def test_eval_native():
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from swift import EvalArguments, eval_main
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eval_main(
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EvalArguments(
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model='Qwen/Qwen2.5-0.5B-Instruct',
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eval_dataset='arc',
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infer_backend=infer_backend,
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eval_backend='Native',
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eval_limit=10,
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eval_generation_config={
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'max_new_tokens': 128,
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'temperature': 0.1
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},
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extra_eval_args={'ignore_errors': False},
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))
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def test_eval_llm():
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from swift import EvalArguments, eval_main
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eval_main(
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EvalArguments(
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model='Qwen/Qwen2.5-0.5B-Instruct',
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eval_dataset='arc_c',
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infer_backend=infer_backend,
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eval_backend='OpenCompass',
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eval_limit=10))
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def test_eval_mllm():
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from swift import EvalArguments, eval_main
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eval_main(
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EvalArguments(
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model='Qwen/Qwen2.5-VL-3B-Instruct',
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eval_dataset=['realWorldQA'],
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infer_backend='transformers',
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eval_backend='VLMEvalKit',
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eval_limit=10,
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eval_generation_config={
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'max_new_tokens': 128,
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'temperature': 0.1
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}))
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def test_eval_url():
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from swift import DeployArguments, EvalArguments, eval_main
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from swift.pipelines import run_deploy
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deploy_args = DeployArguments(model='Qwen/Qwen2-VL-7B-Instruct', infer_backend=infer_backend, verbose=False)
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with run_deploy(deploy_args, return_url=True) as url:
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eval_main(EvalArguments(model='Qwen2-VL-7B-Instruct', eval_url=url, eval_dataset=['arc']))
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if __name__ == '__main__':
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test_eval_llm()
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# test_eval_mllm()
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# test_eval_url()
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# test_eval_native()
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