Starling-LM-7B-beta

Starling-LM-7B-beta is a large language model developed by the Nexusflow Team to improve helpfulness and harmlessness in language interactions. This AI-powered tool is designed to enhance performance in generating responses across various applications, including multi-turn conversations and coding assistance.

Key features:
- Language Model Finetuning: Enhanced performance through finetuning from Openchat-3.5-0106 using Reinforcement Learning from AI Feedback (RLAIF).
- Policy Optimization: Utilizes Fine-Tuning Language Models from Human Preferences (PPO) method for optimizing model responses.
- Multi-turn Conversations: Supports extended dialogues for more complex interactions.
- Coding Mode: Assists with coding tasks, such as implementing algorithms in C++.
- Performance Improvement: Demonstrates enhanced capabilities compared to its base model.

How it works:
1. Users provide input prompts to interact with the model.
2. The model processes these prompts using a specific chat template.
3. Responses are generated based on the input, with the option to adjust verbosity through temperature settings.

Integrations:
Hugging Face, LMSYS Chatbot Arena

Use of AI:
Starling-LM-7B-beta employs Reinforcement Learning from AI Feedback (RLAIF) to optimize its performance based on human feedback. It also uses the Fine-Tuning Language Models from Human Preferences (PPO) method for policy optimization.

AI foundation model:
The model is finetuned from Openchat-3.5-0106, which is based on Mistral-7B-v0.1.

Target users:
- Developers seeking assistance with coding tasks
- Researchers working on improving language models and their applications

How to access:
Starling-LM-7B-beta is available for testing on LMSYS Chatbot Arena and can be accessed through the Hugging Face API. It is licensed under the Apache-2.0 license, allowing for open-source use under certain conditions.