Instructions to use manarea/prueba1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manarea/prueba1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="manarea/prueba1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("manarea/prueba1") model = AutoModelForSequenceClassification.from_pretrained("manarea/prueba1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a8a7171f84f613767e73d9654b43ab16b11cda1e15228bd8e28590a22293983
- Size of remote file:
- 211 MB
- SHA256:
- 0eca68e654bd035766f1f21eefab710e9a73a477b8295fa4081422773f7d48b0
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