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Index-1.9B

A lightweight large language model independently developed by Bilibili

#natural language processing
#machine learning
#role play
#large language model
Index-1.9B

Product Details

The Index-1.9B series is a lightweight large language model independently developed by Bilibili. It includes multiple versions, such as base, pure, chat and character, etc. It is suitable for pre-training of corpus mainly in Chinese and English, and has performed well on multiple evaluation benchmarks. The model supports SFT and DPO alignment, as well as RAG technology for role-play customization, which is suitable for scenarios such as dialogue generation and role-playing.

Main Features

1
Supports multiple pre-trained model versions to adapt to different application scenarios
2
Pre-training on 2.8T Chinese and English corpus, covering a wide range of language data
3
Optimize dialogue generation capabilities through SFT and DPO technology
4
Introducing RAG technology to realize role-playing customization functions
5
Support quantification technology to reduce performance loss and save video memory usage
6
Provide detailed technical reports and usage documents to facilitate developers' understanding and application

How to Use

1
1. Visit the GitHub page, clone or download the Index-1.9B model repository
2
2. Install the required environment and dependencies according to the README.md document
3
3. Select the appropriate model version, such as Index-1.9B-Chat or Index-1.9B-Character
4
4. Use the provided sample code or API interface to load the model and test it
5
5. According to specific application requirements, adjust model parameters and configuration to optimize performance.
6
6. Integrate the model into your own projects to develop dialogue systems or content generation applications
7
7. Refer to the quantization script to quantize the model to reduce video memory usage.

Target Users

The Index-1.9B model is mainly aimed at developers and researchers, especially professionals interested in the fields of natural language processing, machine learning and artificial intelligence. The model's lightweight design and diverse functions make it suitable for application scenarios such as dialogue systems, content generation, role playing, etc., and can help users quickly build intelligent dialogue and interactive systems.

Examples

Used to build an intelligent customer service system and provide 24-hour online question and answer service

Applied to content creation platforms to assist in generating creative copywriting and storylines

Integrated into educational software to provide personalized learning guidance and language practice

Quick Access

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Categories

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› AI model
› AI chatbot

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