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:
- 22493fb9d921875e3e4683b32bd1fba4d6d890069008bfcc7e9035fa2b119715
- Size of remote file:
- 3.58 kB
- SHA256:
- d623fcf59b7b2eb64507152f85e6f32d9fa5e088c8e65f29ba96ceba73dd9563
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