TeamCraft-VLA-7B-Dec is a multi-modal vision-language action model designed for decentralized multi-agent collaborations. The model encodes multi-modal prompts specifying the task, one agent's visual observation and inventory at each timestep to generate actionable output for single agents under multi-agent settings.
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.
-
Primary intended uses:
The primary use of the TeamCraft-VLA-7B-Dec is research on multi-agents under multi-modal settings.
-
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.
-
The model is not designed for real-world decision-making or deployment in safety-critical systems.
-
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.
