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:
- 6482fcaf261b1d4815c6c79ad30120b4687a22b5f2617dae1e9bace3d9603458
- Size of remote file:
- 1.58 GB
- SHA256:
- 89af39b36d5376281b59599ff3869318af47ee59408bd1cc6cd55d5c52d9c170
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