TeamCraft-VLA-7B-Cen is a multi-modal vision-language action model designed for centralized multi-agent collaborations. The model encodes multi-modal prompts specifying the task, visual observations, and agent inventory information at each timestep to generate actionable outputs.
We provide a full environment with detailed running instruction on
GitHub.
The TeamCraft-VLA (Vision-Language-Action) architecture integrates a CLIP ViT-L/14 visual encoder with a linear projector for modality alignment and Vicuna-v1.5-7B (Llama 2.0) as the LLM backbone, combining visual and text embeddings to generate actions for multi-agent tasks.
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Primary intended uses:
The primary use of the TeamCraft-VLA-7B-Cen is research on multi-agents under multi-modal settings.
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Primary intended users:
The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, multi-agent system, and artificial intelligence.
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The model is not designed for real-world decision-making or deployment in safety-critical systems.
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The model not be used for tasks requiring ethical reasoning, moral judgments, or any applications where improper actions could lead to harm or violation of regulations.
Llama 2 is licensed under the LLAMA 2 Community License,
Copyright (c) Meta Platforms, Inc. All Rights Reserved.
