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1c8c2d9ab3
* move old s2s scripts to legacy * add the tests back * proper rename * restore * Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Stas Bekman <stas@stason.org> Co-authored-by: Stas Bekman <stas00@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
40 lines
1.5 KiB
Python
Executable File
40 lines
1.5 KiB
Python
Executable File
#!/usr/bin/env python
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# Copyright 2020 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import fire
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from transformers import AutoConfig, AutoModelForSeq2SeqLM, AutoTokenizer
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def save_randomly_initialized_version(config_name: str, save_dir: str, **config_kwargs):
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"""Save a randomly initialized version of a model using a pretrained config.
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Args:
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config_name: which config to use
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save_dir: where to save the resulting model and tokenizer
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config_kwargs: Passed to AutoConfig
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Usage::
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save_randomly_initialized_version("facebook/bart-large-cnn", "distilbart_random_cnn_6_3", encoder_layers=6, decoder_layers=3, num_beams=3)
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"""
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cfg = AutoConfig.from_pretrained(config_name, **config_kwargs)
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model = AutoModelForSeq2SeqLM.from_config(cfg)
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model.save_pretrained(save_dir)
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AutoTokenizer.from_pretrained(config_name).save_pretrained(save_dir)
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return model
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if __name__ == "__main__":
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fire.Fire(save_randomly_initialized_version)
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