Instructions to use emilys/BERTweet-WNUT17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emilys/BERTweet-WNUT17 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="emilys/BERTweet-WNUT17")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("emilys/BERTweet-WNUT17") model = AutoModelForTokenClassification.from_pretrained("emilys/BERTweet-WNUT17") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2b7ace44ca584cb48e18bd1dd7180ceb0d59812c688d8e9b92e755516006076
- Size of remote file:
- 537 MB
- SHA256:
- 283dbc5e102ab26b68de27a9234c5c11c980085e9166b9779c4fa26778c1a41a
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