Instructions to use AntoineBlanot/roberta-span-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AntoineBlanot/roberta-span-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AntoineBlanot/roberta-span-detection")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AntoineBlanot/roberta-span-detection") model = AutoModel.from_pretrained("AntoineBlanot/roberta-span-detection") - Notebooks
- Google Colab
- Kaggle
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README.md
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# RoBERTa Span Detection
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This model is a fine-tuned model of [roberta-large](https://huggingface.co/roberta-large) after being trained on a **mixture of NER datasets**.
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Basically, this model
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- 'B-TAG': beginning token of span
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- 'I-TAG': inside token of span
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- 'O': token not a span
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# RoBERTa Span Detection
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This model is a fine-tuned model of [roberta-large](https://huggingface.co/roberta-large) after being trained on a **mixture of NER datasets**.
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Basically, this model can detect NER spans (with <u>no differenciation on classes</u>). Labels use the IBO format and are:
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- 'B-TAG': beginning token of span
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- 'I-TAG': inside token of span
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- 'O': token not a span
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