Instructions to use dpravinv/fold_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dpravinv/fold_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dpravinv/fold_4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dpravinv/fold_4") model = AutoModelForSequenceClassification.from_pretrained("dpravinv/fold_4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dpravinv/fold_4: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/dpravinv/fold_4/resolve/main/training_args.bin
- Command line
-
hf download hf://dpravinv/fold_4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dpravinv/fold_4/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- f330e81546f5390ac3df28b77b86e3c7c3aecf9926cdadcc8ab67276a528383e
- Size of remote file:
- 5.43 kB
- SHA256:
- 4a984219d430e6b6c2fbd1c06d1db57d91bf497a0022495613bb26b3d5940d78
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