Instructions to use uhhlt/binary-compqa-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uhhlt/binary-compqa-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="uhhlt/binary-compqa-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("uhhlt/binary-compqa-classifier") model = AutoModelForSequenceClassification.from_pretrained("uhhlt/binary-compqa-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from uhhlt/binary-compqa-classifier: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/uhhlt/binary-compqa-classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://uhhlt/binary-compqa-classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/uhhlt/binary-compqa-classifier/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- fe9545457ce2c1fa0510ffc85ad3ec3e1fcf926cd0e5b4dd9e6f2f456a355649
- Size of remote file:
- 268 MB
- SHA256:
- bbc64b6cbc27ddf5501e3930bbce17bb65569e227670878192ac2d494f45f90d
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