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What is Vicuna?

Vicuna-13B is a conversational AI created by fine-tuning LLaMA on a collection of user dialogues sourced from ShareGPT. Early evaluations, using GPT-4 as a benchmark, suggest that Vicuna-13B reaches over 90% of the performance level found in OpenAI's ChatGPT and Google Bard, while outperforming other models like LLaMA and Stanford Alpaca in more than 90% of tested cases. The estimated cost to train Vicuna-13B is around $300, which is quite economical for a model of its caliber. Furthermore, the model's source code and weights are publicly accessible under non-commercial licenses, promoting a spirit of collaboration and further development. This level of transparency not only fosters innovation but also allows users to delve into the model's functionalities across various applications, paving the way for new ideas and enhancements. Ultimately, such initiatives can significantly contribute to the advancement of conversational AI technologies.

What is StableVicuna?

StableVicuna is the first large-scale open-source chatbot that has been developed utilizing reinforced learning from human feedback (RLHF). Building on the Vicuna v0 13b model, it has undergone significant enhancements through further instruction fine-tuning and additional RLHF training. By employing Vicuna as its core model, StableVicuna follows a rigorous three-phase RLHF framework as outlined by researchers Steinnon et al. and Ouyang et al. To achieve its remarkable performance, we engage in further training of the base Vicuna model through supervised fine-tuning (SFT), drawing from a combination of three unique datasets. The first dataset utilized is the OpenAssistant Conversations Dataset (OASST1), which contains 161,443 human-contributed messages organized into 66,497 conversation trees across 35 different languages. The second dataset, known as GPT4All Prompt Generations, includes 437,605 prompts along with responses generated by the GPT-3.5 Turbo model. The final dataset is the Alpaca dataset, featuring 52,000 instructions and examples derived from OpenAI's text-davinci-003 model. This multifaceted training strategy significantly bolsters the chatbot's capability to interact meaningfully across a variety of conversational scenarios, setting a new standard for open-source conversational AI.

Media

Media

Integrations Supported

AI Collective
LM Studio
Prem AI
WebLLM

Integrations Supported

API Availability

API Availability

Pricing Information

Free
Open source
Free Version

Pricing Information

Free
Free Version

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

lmsys.org

Date Founded

2023

Company Website

lmsys.org

Company Facts

Organization Name

Stability AI

Date Founded

2019

Company Location

United Kingdom

Company Website

stability.ai/

Categories and Features

AI Chatbots

Not specified

AI Models

Not specified

Large Language Models

Not specified

Categories and Features

Chatbot

Not specified

Conversational AI

Not specified

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