Update README.md

README.md

@@ -10,4 +10,50 @@ tags:
 - RLHF
 - conversational
 - reward model
----
+---
+
+---
+license: apache-2.0
+datasets:
+- berkeley-nest/Nectar
+language:
+- en
+library_name: transformers
+tags:
+- reward model
+- RLHF
+- RLAIF
+---
+# Starling-LM-7B-beta-GGUF
+
+- Model creator: [Nexusflow](https://huggingface.co/Nexusflow)
+- Original model: [Starling-LM-7B-beta](https://huggingface.co/Nexusflow/Starling-LM-7B-beta) 
+
+<!-- description start -->
+## Description
+
+This repo contains GGUF format model files for [Starling-LM-7B-beta](https://huggingface.co/Nexusflow/Starling-LM-7B-beta) 
+
+**Model Summary**
+<!-- Provide a quick summary of what the model is/does. -->
+
+- **Developed by: The Nexusflow Team (** Banghua Zhu * , Evan Frick * , Tianhao Wu * , Hanlin Zhu, Karthik Ganesan, Wei-Lin Chiang, Jian Zhang, and Jiantao Jiao).
+- **Model type:** Language Model finetuned with RLHF / RLAIF
+- **License:** Apache-2.0 license under the condition that the model is not used to compete with OpenAI
+- **Finetuned from model:** [Openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106) (based on [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1))
+ 
+
+We introduce Starling-LM-7B-beta, an open large language model (LLM) trained by Reinforcement Learning from AI Feedback (RLAIF). Starling-LM-7B-beta is trained from [Openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106) with our new reward model [Nexusflow/Starling-RM-34B](https://huggingface.co/Nexusflow/Starling-RM-34B) and policy optimization method [Fine-Tuning Language Models from Human Preferences (PPO)](https://arxiv.org/abs/1909.08593).
+Harnessing the power of the ranking dataset, [berkeley-nest/Nectar](https://huggingface.co/datasets/berkeley-nest/Nectar), the upgraded reward model, [Starling-RM-34B](https://huggingface.co/Nexusflow/Starling-RM-34B), and the new reward training and policy tuning pipeline, Starling-LM-7B-beta scores an improved 8.12 in MT Bench with GPT-4 as a judge. 
+
+
+## Citation
+```
+@misc{starling2023,
+    title = {Starling-7B: Improving LLM Helpfulness & Harmlessness with RLAIF},
+    url = {},
+    author = {Zhu, Banghua and Frick, Evan and Wu, Tianhao and Zhu, Hanlin and Ganesan, Karthik and Chiang, Wei-Lin and Zhang, Jian and Jiao, Jiantao},
+    month = {November},
+    year = {2023}
+}
+```