Instructions to use Jeevesh8/6ep_bert_ft_cola-21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/6ep_bert_ft_cola-21 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/6ep_bert_ft_cola-21")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/6ep_bert_ft_cola-21") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/6ep_bert_ft_cola-21", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jeevesh8/6ep_bert_ft_cola-21: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-21/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jeevesh8/6ep_bert_ft_cola-21/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-21/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- d28264b6d4946487a0eb4819e04e6443524abb7d9b50cfb4f06825022a7ae0d5
- Size of remote file:
- 438 MB
- SHA256:
- 371a3eb53114eceb2569ee5649d6d7563019646ff3804422b4ec4074e77a4b47
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