LargeWorldModel/LWM

Health v2 · maintenance only

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7425 stars · 563 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Large World Model (LWM) is a family of open-source 7B-parameter multimodal autoregressive transformer models trained on long videos and books with RingAttention, supporting context up to 1M tokens. The repository provides training and inference code for language, image, and video understanding and generation.

Use cases

• answer questions about hour-long YouTube videos
• retrieve facts across a 1M-token context
• chat with images and videos
• generate videos and images from text
• train transformers on million-length multimodal sequences
• process entire books with a large-context language model

When to choose

• you need a model that understands very long videos or documents
• you want open weights for million-token-context multimodal research
• you need a reference implementation of RingAttention and masked sequence packing

When to avoid

• you need a production-ready, well-supported inference stack
• you only need short-context text chat
• you lack multi-GPU resources, since training targets large clusters

Facets

library · maturity active

machine-learning deep-learning llm-training llm-inference video-processing nlp large-language-models deep-learning machine-learning python multimodal ring-attention long-context vision-language-model video-understanding research video natural-language-processing linux gpu

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For agents

markdown · JSON · MCP: product_card(name="LargeWorldModel/LWM")