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50 lines
1.9 KiB
Python
50 lines
1.9 KiB
Python
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# Copyright (c) Alibaba, Inc. and its affiliates.
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import unittest
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from modelscope.hub.snapshot_download import snapshot_download
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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class TextPlugGenerationTest(unittest.TestCase):
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def setUp(self) -> None:
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# please make sure this local path exists.
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self.model_id = 'damo/nlp_plug_text-generation_27B'
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self.model_dir = snapshot_download(self.model_id)
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self.plug_input = '段誉轻挥折扇，摇了摇头，说道：“你师父是你的师父，你师父可不是我的师父。"'
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@unittest.skip('distributed plug, skipped')
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def test_plug(self):
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""" The model can be downloaded from the link on
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https://modelscope.cn/models/damo/nlp_plug_text-generation_27B/summary.
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After downloading, you should have a plug model structure like this:
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nlp_plug_text-generation_27B
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|_ config.json
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|_ configuration.json
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|_ ds_zero-offload_10B_config.json
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|_ vocab.txt
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|_ model <-- an empty directory
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Model binaries shall be downloaded separately to populate the model directory, so that
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the model directory would contain the following binaries:
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|_ model
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|_ mp_rank_00_model_states.pt
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|_ mp_rank_01_model_states.pt
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|_ mp_rank_02_model_states.pt
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|_ mp_rank_03_model_states.pt
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|_ mp_rank_04_model_states.pt
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|_ mp_rank_05_model_states.pt
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|_ mp_rank_06_model_states.pt
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|_ mp_rank_07_model_states.pt
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"""
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# download model binaries to <model_dir>/model
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pipe = pipeline(Tasks.text_generation, model=self.model_id)
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print(
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f'input: {self.plug_input}\noutput: {pipe(self.plug_input, out_length=256)}'
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)
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if __name__ == '__main__':
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unittest.main()
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