VideoLLaMA3-7B
by DAMO-NLP-SG
Video understanding foundation model with efficient long-video processing
DAMO-NLP-SG/VideoLLaMA3-7Bmixpeek://video_extractor@v1/damo_videollama3_7b_v1Overview
VideoLLaMA3 is a frontier multimodal model for image and video understanding from Alibaba DAMO Academy. It uses a vision-centric architecture with a 4-stage training pipeline including video-centric fine-tuning.
The model reduces vision tokens based on frame similarity for efficient long-video processing, making it practical for indexing hours of footage without proportional compute cost.
Architecture
7B parameter model with vision-centric design. 4-stage training: image pretraining → image SFT → video pretraining → video SFT. Adaptive token reduction based on inter-frame similarity for long videos.
Mixpeek SDK Integration
mixpeek.ingest.from_url(url="s3://footage/episode.mp4",collection="video_archive",feature_extractors=[{"type": "caption","model": "mixpeek://video_extractor@v1/damo_videollama3_7b_v1"}])
Capabilities
- Video comprehension
- Image understanding
- Long-video processing
- Scene description
- Video QA
- Temporal reasoning
Use Cases on Mixpeek
Performance
Common Pipeline Companions
Specification
Build a pipeline with VideoLLaMA3-7B
Add this model to a processing pipeline alongside other extractors. Combine with retrieval stages for end-to-end search.
Open Studio