internlm

Large language model system supporting multimodal understanding, long-context dialogue, and 3D scene reconstruction

Research Tools Developer Tools Education Assistant Text to Image Large Language Models (LLMs)

Overview Alternatives

Monthly Visits

31.1K

Avg. Session Duration

1 min

Category Rank

N/A

Bounce Rate

0.4%

What is internlm?

The ShuSheng General Large Model is a comprehensive large language model system developed collaboratively by Shanghai AI Laboratory, SenseTime, and multiple universities. The system comprises three core models: ShuSheng General Large Model M (a 200-billion-parameter multimodal model), ShuSheng General Large Model-Chat (a language model supporting 8K context), and ShuSheng General Large Model-XComposer (a 3D scene reconstruction model). Built on a fully open-source end-to-end architecture, it covers the entire workflow from data processing and model training to inference deployment, enabling researchers and developers to easily customize and integrate the system.

Key Features of internlm?

Multimodal Understanding

The Tongyi Qianwen large model M has the capability to process text, images, and videos, featuring 20 billion parameters, trained on over 8 billion multimodal samples, supporting 3.5 million semantic labels that cover real-world concepts.

Full-Stack Open Source

A complete open development ecosystem, including data processing tools, training frameworks, fine-tuning tools, and deployment solutions, accompanied by comprehensive documentation and community support.

Cross-Modal Generation

Advanced capabilities for conversion across different modalities, such as generating poetry from images or creating images from text, enabling cross-modal creativity.

Extended Context Support

The Tongyi Qianwen-Chat model supports an 8K context length, suitable for long-text conversations and document processing, enabling complex reasoning and extended dialogues.

Interactive Interface

Supports intuitive interaction methods such as cursor clicks and natural language commands, lowering the barrier for AI task operations and catering to a broader user base.

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internlm