Video-Text-to-Text
Transformers
Safetensors
English
Chinese
moss_vl
feature-extraction
Realtime
Streaming
Video-Understanding
Image-Understanding
MOSS-VL
OpenMOSS
multimodal
video
vision-language
custom_code
Instructions to use OpenMOSS-Team/MOSS-VL-Realtime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMOSS-Team/MOSS-VL-Realtime with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenMOSS-Team/MOSS-VL-Realtime", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Unify MOSS-VL processor and inference preprocessing defaults
Verified signatureUse the shared processor and tokenizer, set image/video pixel budgets to 201326592, and disable vision tail padding with vision_seq_pad_multiple=1. Preserve model implementation and weights.5b97f7a
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Upload MOSS-VL-Realtime-0708 release
Verified signaturef55d7c8