Instructions to use Tommert25/MultiBERTBestModelOct13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tommert25/MultiBERTBestModelOct13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Tommert25/MultiBERTBestModelOct13")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Tommert25/MultiBERTBestModelOct13") model = AutoModelForTokenClassification.from_pretrained("Tommert25/MultiBERTBestModelOct13", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f4b877e47919472bae6410787b216e140956a14410396f6d59b57fc886b0610
- Size of remote file:
- 4.09 kB
- SHA256:
- 0539bd0e57c29be40ca064edca77a6f0ae368317f05a01497223c4fc4d21c110
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