Instructions to use RajuEEE/RewardModelOnlyOnAnswer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RajuEEE/RewardModelOnlyOnAnswer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RajuEEE/RewardModelOnlyOnAnswer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RajuEEE/RewardModelOnlyOnAnswer") model = AutoModelForSequenceClassification.from_pretrained("RajuEEE/RewardModelOnlyOnAnswer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from RajuEEE/RewardModelOnlyOnAnswer: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/RajuEEE/RewardModelOnlyOnAnswer/resolve/main/training_args.bin
- Command line
-
hf download hf://RajuEEE/RewardModelOnlyOnAnswer/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/RajuEEE/RewardModelOnlyOnAnswer/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- c3622da96a59496e3a828f4de158474129e2c2cb50390874ba6b748d07c6d384
- Size of remote file:
- 4.09 kB
- SHA256:
- 3ce364aaea99805a9d8b096553ad8eda72131b32d7bd79406d84977f745a2a1e
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