Video Classification
Transformers
Safetensors
English
qwen3_vl
video
video-editing
reward-model
vlm
qwen3-vl
Instructions to use viskoplatform/VEFX-Reward-32B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use viskoplatform/VEFX-Reward-32B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="viskoplatform/VEFX-Reward-32B")# Load model directly from transformers import AutoProcessor, Qwen3VLRewardModelBT processor = AutoProcessor.from_pretrained("viskoplatform/VEFX-Reward-32B") model = Qwen3VLRewardModelBT.from_pretrained("viskoplatform/VEFX-Reward-32B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5356900ae65bd47f1f9a10a7c3bcb2287b0aa88ec58d11909efb8d0609ed210
- Size of remote file:
- 11.4 MB
- SHA256:
- a8b0df0711162c6a57d874db3082a5e428c13f046ffadd9ad0957dae10588950
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