Instructions to use manarea/Intercalado-ID23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manarea/Intercalado-ID23 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="manarea/Intercalado-ID23")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("manarea/Intercalado-ID23") model = AutoModelForSequenceClassification.from_pretrained("manarea/Intercalado-ID23", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d15ce2f411ae37d26815c8d1acdada37eb062c9d7fd2f30b1505b8975d549279
- Size of remote file:
- 239 MB
- SHA256:
- 70201c649f4aeb65c3f42e080610e0bcd413c27f10056fc22799b5b5afa9c9d1
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