Instructions to use rppadmakumar/fever_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rppadmakumar/fever_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rppadmakumar/fever_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rppadmakumar/fever_model") model = AutoModelForSequenceClassification.from_pretrained("rppadmakumar/fever_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rppadmakumar/fever_model: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/rppadmakumar/fever_model/resolve/main/training_args.bin
- Command line
-
hf download hf://rppadmakumar/fever_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rppadmakumar/fever_model/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- 0bbd5f47c49af2cce6c00217d71174447443b2000febf1a471f0b9eb8ca1a73f
- Size of remote file:
- 4.86 kB
- SHA256:
- f085e9315c60551ed0c6aea92c8e3778c7b2059a36b202b223c8d1dcb6643093
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