Instructions to use manarea/prueba2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manarea/prueba2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="manarea/prueba2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("manarea/prueba2") model = AutoModelForSequenceClassification.from_pretrained("manarea/prueba2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9944d1cb4413049664daa065e91c88053476bafdd53b1276164aa5d474126cf2
- Size of remote file:
- 268 MB
- SHA256:
- a8d00fafcb04a8a9dbb1e2b894818affa6aef44c3754db46297ff0e3f4d17e75
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