Instructions to use manarea/2-Intercalado-ID23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manarea/2-Intercalado-ID23 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="manarea/2-Intercalado-ID23")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("manarea/2-Intercalado-ID23") model = AutoModelForSequenceClassification.from_pretrained("manarea/2-Intercalado-ID23", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09389ba6535b940c7078cc98f9400a7e1af600afffc5c814ada9086d6d6e9928
- Size of remote file:
- 239 MB
- SHA256:
- f9e2b614412f6aeb7b8d7073abf99ae31911c13fa2a26bb86d6c3fa59e2cc9ad
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