Instructions to use btan2/cappy-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use btan2/cappy-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="btan2/cappy-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("btan2/cappy-large") model = AutoModelForSequenceClassification.from_pretrained("btan2/cappy-large") - Notebooks
- Google Colab
- Kaggle
Upload pytorch_model.bin
Browse files- pytorch_model.bin +3 -0
pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:12c75d1559962148fbaeec6afebdd4657cdf2777fa12b36763c12ee5044ac4cd
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size 1421573614
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