Video-Text-to-Text
Transformers
Safetensors
English
qwen3_vl
image-text-to-text
video-understanding
reward-model
computer-use
qwen3-vl
multimodal
Instructions to use lime-nlp/ExeVRM-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lime-nlp/ExeVRM-8B with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("lime-nlp/ExeVRM-8B") model = AutoModelForImageTextToText.from_pretrained("lime-nlp/ExeVRM-8B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d072cb0342bf1fab39b963d090d876e8afae39760a3ecda0a288423fd987118
- Size of remote file:
- 8.47 kB
- SHA256:
- be9588760059542c4c240f656c5e98b735f5f457b0d5ac1b5651204c27b856d5
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