Instructions to use RajuEEE/RewardModel_TwoLabels_OnlyOnAnswer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RajuEEE/RewardModel_TwoLabels_OnlyOnAnswer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RajuEEE/RewardModel_TwoLabels_OnlyOnAnswer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RajuEEE/RewardModel_TwoLabels_OnlyOnAnswer") model = AutoModelForSequenceClassification.from_pretrained("RajuEEE/RewardModel_TwoLabels_OnlyOnAnswer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from RajuEEE/RewardModel_TwoLabels_OnlyOnAnswer: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/RajuEEE/RewardModel_TwoLabels_OnlyOnAnswer/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://RajuEEE/RewardModel_TwoLabels_OnlyOnAnswer@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/RajuEEE/RewardModel_TwoLabels_OnlyOnAnswer/resolve/refs%2Fpr%2F1/model.safetensors
438 MB
- Xet hash:
- 03d4db9706864e0cab7c2a66dd4d69d317b768d310469da250f101e59323c00f
- Size of remote file:
- 438 MB
- SHA256:
- 8e381e086935105c9bd9923d453484873c91a085eb3d4ab6a25755192d21d35f
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