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 # Warning: Pipeline type "image-to-image" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("image-to-image", model="Video-Reason/VBVR-Pro-BAGEL")# pip install -U transformers accelerate # Load model directly from transformers import Bagel model = Bagel.from_pretrained("Video-Reason/VBVR-Pro-BAGEL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Video-Reason/VBVR-Pro-BAGEL: direct link, hf CLI and curl.
- Browser
- Download file 29.2 GB
-
https://huggingface.co/Video-Reason/VBVR-Pro-BAGEL/resolve/main/model.safetensors
- Command line
-
hf download hf://Video-Reason/VBVR-Pro-BAGEL/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Video-Reason/VBVR-Pro-BAGEL/resolve/main/model.safetensors
29.2 GB
- Xet hash:
- 244a9d2d6ed1a6d8c11a9c44ea036f5b16f369f9a0db053dd9b4344ab003652f
- Size of remote file:
- 29.2 GB
- SHA256:
- 60662ee31111ab045b52f77739893c65d378b90b07a7af9c697f29428c7c4c8b
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