Instructions to use Jeevesh8/bert_ft_cola-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-2") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jeevesh8/bert_ft_cola-2: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Jeevesh8/bert_ft_cola-2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jeevesh8/bert_ft_cola-2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jeevesh8/bert_ft_cola-2/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 8cba18109f243d418c2a4af005f0dd38bf3322768c2b771aa1873f9a0eca676d
- Size of remote file:
- 438 MB
- SHA256:
- 0dd60c3f5930b5718567fb927dbd7ff88a53eb2fabe8b84fc503e721c51fe4dd
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