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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harun27/binary_paragraph") model = AutoModelForSequenceClassification.from_pretrained("harun27/binary_paragraph", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from harun27/binary_paragraph: direct link, hf CLI and curl.
- Browser
- Download file 3.58 MB
-
https://huggingface.co/harun27/binary_paragraph/resolve/e69964d72bb371d5243d39f2d6085eb8938d7338/tokenizer.json
- Command line
-
hf download hf://harun27/binary_paragraph@e69964d72bb371d5243d39f2d6085eb8938d7338/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/harun27/binary_paragraph/resolve/e69964d72bb371d5243d39f2d6085eb8938d7338/tokenizer.json
3.58 MB
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