Instructions to use cuadron11/modelBsc5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cuadron11/modelBsc5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="cuadron11/modelBsc5")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("cuadron11/modelBsc5") model = AutoModelForTokenClassification.from_pretrained("cuadron11/modelBsc5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 683d6d113e6e7f8309b0918be9ce3886db354b8f29c21f08be0bf799c4d8b71f
- Size of remote file:
- 496 MB
- SHA256:
- ccab26e04a0b31953286733a55cad905d7424bfbe9120706291d9607a09d9221
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