Instructions to use Fujitsu/pytorrent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fujitsu/pytorrent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Fujitsu/pytorrent")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Fujitsu/pytorrent") model = AutoModel.from_pretrained("Fujitsu/pytorrent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -24,6 +24,7 @@ tokenizer = AutoTokenizer.from_pretrained("Fujitsu/pytorrent")
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model = AutoModel.from_pretrained("Fujitsu/pytorrent")
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```
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## Citation
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```
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@misc{bahrami2021pytorrent,
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title={PyTorrent: A Python Library Corpus for Large-scale Language Models},
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primaryClass={cs.SE},
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howpublished={https://arxiv.org/abs/2110.01710},
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}
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```
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model = AutoModel.from_pretrained("Fujitsu/pytorrent")
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```
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## Citation
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Preprint: [https://arxiv.org/abs/2110.01710](https://arxiv.org/abs/2110.01710)
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```
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@misc{bahrami2021pytorrent,
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title={PyTorrent: A Python Library Corpus for Large-scale Language Models},
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primaryClass={cs.SE},
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howpublished={https://arxiv.org/abs/2110.01710},
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}
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```
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