Instructions to use aimarsg/prueba5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aimarsg/prueba5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="aimarsg/prueba5")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("aimarsg/prueba5") model = AutoModelForTokenClassification.from_pretrained("aimarsg/prueba5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64da5a1604520ca1e1e24111803a19e6a0f208107d554eb95922664e89f1d7ca
- Size of remote file:
- 3.52 kB
- SHA256:
- 76cc8c05abeb85342860212b64ad634ece7f7f29df8361e29f28e9eeb30b562c
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