Image-to-Image
Transformers
Safetensors
bagel
image-editing
image-generation
interleaved-generation
vbvr-pro
Instructions to use Video-Reason/VBVR-Pro-BAGEL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Video-Reason/VBVR-Pro-BAGEL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-to-image", model="Video-Reason/VBVR-Pro-BAGEL")# Load model directly from transformers import Bagel model = Bagel.from_pretrained("Video-Reason/VBVR-Pro-BAGEL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 205 Bytes
746f116 | 1 2 3 4 5 6 7 8 9 10 | {
"hidden_size": 1152,
"image_size": 980,
"intermediate_size": 4304,
"model_type": "siglip_vision_model",
"num_attention_heads": 16,
"num_hidden_layers": 27,
"patch_size": 14
}
|