Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use SaketR1/bias-reward-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaketR1/bias-reward-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SaketR1/bias-reward-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SaketR1/bias-reward-model") model = AutoModelForSequenceClassification.from_pretrained("SaketR1/bias-reward-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SaketR1/bias-reward-model: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/SaketR1/bias-reward-model/resolve/main/training_args.bin
- Command line
-
hf download hf://SaketR1/bias-reward-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SaketR1/bias-reward-model/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- 29cb08973ec20e604c2f92af74c265f5ae9e183dfe12e281a002ef71eb7e0c47
- Size of remote file:
- 5.78 kB
- SHA256:
- db91522bde673ab2a45d76ea5efdc6dfa4a5cc84f03c1e3b55aff56fefa6bec9
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