Instructions to use marshmellow77/roberta-base-cuad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marshmellow77/roberta-base-cuad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="marshmellow77/roberta-base-cuad", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("marshmellow77/roberta-base-cuad") model = AutoModelForQuestionAnswering.from_pretrained("marshmellow77/roberta-base-cuad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Heiko Hotz commited on
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README.md
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Link for model checkpoint: https://github.com/TheAtticusProject/cuad
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For the use of the model with CUAD: https://github.com/marshmellow77/cuad-demo
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and https://huggingface.co/spaces/marshmellow77/contract-review
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Link for model checkpoint: https://github.com/TheAtticusProject/cuad
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For the use of the model with CUAD: https://github.com/marshmellow77/cuad-demo
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and https://huggingface.co/spaces/marshmellow77/contract-review
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Related blog posts:
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- https://towardsdatascience.com/how-to-set-up-a-machine-learning-model-for-legal-contract-review-fe3b48b05a0e
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- https://towardsdatascience.com/how-to-set-up-a-machine-learning-model-for-legal-contract-review-part-2-6ecbbe680ba
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