Update README.md

README.md

@@ -1,3 +1,46 @@
----
-license: mit
----
+---
+license: mit
+---
+
+# Introduction
+This reward model is finetuned from the [Ray2333/GRM-llama3-8B-sftreg](https://huggingface.co/Ray2333/GRM-llama3-8B-sftreg) using the [Skywork preference dataset](https://huggingface.co/datasets/Skywork/Skywork-Reward-Preference-80K-v0.1). 
+
+
+## Usage
+
+```
+import torch
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+device = 'cuda:0'
+# load model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained('Ray2333/GRM-Llama3-8B-rewardmodel-ft')
+reward_model = AutoModelForSequenceClassification.from_pretrained(
+                'Ray2333/GRM-Llama3-8B-rewardmodel-ft', torch_dtype=torch.float16, 
+                device_map=device,
+                )
+message = [
+  {'role': 'user', 'content': "I'm going to go out to a movie, but I need someone to chat with my daughter and pretend to be me while she's home alone.  But I can't do that while I'm at the movie.  Can you help by impersonating me by chat with her?"},
+  {'role': 'assistant', 'content': "Sorry, I'm not comfortable impersonating you in that way.  I'm not willing to behave so dishonestly.  Maybe you can just find a way to bring her to the movie, or you can find a babysitter?"}
+]
+message_template = tokenizer.apply_chat_template(message, tokenize=False)
+
+kwargs = {"padding": 'max_length', "truncation": True, "return_tensors": "pt"}
+tokens = tokenizer.encode_plus(message_template, **kwargs)
+
+with torch.no_grad():
+  reward_tensor = reward_model(tokens["input_ids"][0].view(1,-1).to(device), attention_mask=tokens["attention_mask"][0].view(1,-1).to(device))[0]
+  reward = reward_tensor.cpu().detach().item()
+```
+
+
+## Citation
+If you find this model helpful for your research, please cite GRM
+```
+@article{yang2024regularizing,
+  title={Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs},
+  author={Yang, Rui and Ding, Ruomeng and Lin, Yong and Zhang, Huan and Zhang, Tong},
+  journal={arXiv preprint arXiv:2406.10216},
+  year={2024}
+}
+```