Instructions to use aimarsg/prueba3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aimarsg/prueba3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="aimarsg/prueba3")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("aimarsg/prueba3") model = AutoModelForTokenClassification.from_pretrained("aimarsg/prueba3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a5f37475098f4a4ff45cf6def9e28260da85d5a49f7478f74bbe9b20231f54d
- Size of remote file:
- 496 MB
- SHA256:
- 5c2e650a70f0c7a76f9edfac3d35e0f688be293d77797cd4a0bb7903e22a8ab8
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