Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use harun27/binary_paragraph with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harun27/binary_paragraph with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harun27/binary_paragraph")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harun27/binary_paragraph") model = AutoModelForSequenceClassification.from_pretrained("harun27/binary_paragraph") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bcf01c306dd4fd025ffe6204bc3fe81e541b84b7f0076c2ee80684337659c49d
- Size of remote file:
- 5.37 kB
- SHA256:
- 092fd66ad885078059247ba2ceb901a32cad9a11d0125047d31e07bbc2172390
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