Instructions to use tals/roberta_python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tals/roberta_python with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tals/roberta_python")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tals/roberta_python") model = AutoModelForMaskedLM.from_pretrained("tals/roberta_python") - Notebooks
- Google Colab
- Kaggle
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# BibTeX entry and citation info
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```bibtex
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@
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year={2021},
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archivePrefix={arXiv},
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url={https://arxiv.org/abs/2106.05784}
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}
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```
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# BibTeX entry and citation info
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```bibtex
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@inproceedings{
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schuster2021programming,
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title={Programming Puzzles},
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author={Tal Schuster and Ashwin Kalyan and Alex Polozov and Adam Tauman Kalai},
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booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 1)},
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year={2021},
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url={https://openreview.net/forum?id=fe_hCc4RBrg}
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}
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```
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