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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b90509db2df265bb631dfe8f5dc790c3a9786f4c5e7aab1924460a6d25c5210d
- Size of remote file:
- 496 MB
- SHA256:
- 533c9a513e7d6a9061fc048a6a5ef61c94e8a7e52ddb27b76fd830dd08d149f1
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