Instructions to use aimarsg/prueba1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aimarsg/prueba1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="aimarsg/prueba1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("aimarsg/prueba1") model = AutoModelForTokenClassification.from_pretrained("aimarsg/prueba1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33d601d0ce96c5c5c43f1493ec61f95bd5167bf35278ed3e0e031bcd3e47ac19
- Size of remote file:
- 496 MB
- SHA256:
- d11d1b99de4bc588f12173e0fbc86b38806e209515e7dff7e8040fc0a1a0d819
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