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:
- f9bf331350cc7865b9ccc263847858272ff59d7a9a3929b2df95b48c197f55d6
- Size of remote file:
- 3.52 kB
- SHA256:
- 2056ae60ab6489aabba6cc7a175b6c17fc4c670c8eb97a34e2e79ae6b2ea862b
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