Instructions to use sshreyy/core_classify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshreyy/core_classify with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sshreyy/core_classify")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sshreyy/core_classify") model = AutoModelForSequenceClassification.from_pretrained("sshreyy/core_classify", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54c02fddd21b23ddbc8b61c9a011fc85535bcefcf9a5dd2fd2b863b6dfbc4f45
- Size of remote file:
- 46.8 MB
- SHA256:
- 8bcccdac4623ecd3966f52bc074fb91185617758ada6cd6c283d26c4819c7888
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