Instructions to use Josealssc/resultados_modelo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Josealssc/resultados_modelo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Josealssc/resultados_modelo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Josealssc/resultados_modelo") model = AutoModelForSequenceClassification.from_pretrained("Josealssc/resultados_modelo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad4ef3973a71a0919f90a9fa501a515cf31b812db21af6827b6868fccad95b7f
- Size of remote file:
- 4.86 kB
- SHA256:
- 1d73fb32fd37b49f4a628eb7a81eb178d260bdaf58d5e5e05a30d71f742629aa
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