Instructions to use hchang/reward_modeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hchang/reward_modeling with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("meta-llama/Meta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "hchang/reward_modeling") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from hchang/reward_modeling: direct link, hf CLI and curl.
- Browser
- Download file 9.09 MB
-
https://huggingface.co/hchang/reward_modeling/resolve/main/tokenizer.json
- Command line
-
hf download hf://hchang/reward_modeling/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/hchang/reward_modeling/resolve/main/tokenizer.json
9.09 MB
File too large to display, you can check the raw version instead.