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
Download generation_config.json from Video-Reason/VBVR-Pro-BAGEL: direct link, hf CLI and curl.
- Browser
- Download file 243 Bytes
-
https://huggingface.co/Video-Reason/VBVR-Pro-BAGEL/resolve/main/generation_config.json
- Command line
-
hf download hf://Video-Reason/VBVR-Pro-BAGEL/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/Video-Reason/VBVR-Pro-BAGEL/resolve/main/generation_config.json
243 Bytes
| { | |
| "bos_token_id": 151643, | |
| "pad_token_id": 151643, | |
| "do_sample": true, | |
| "eos_token_id": [ | |
| 151645, | |
| 151643 | |
| ], | |
| "repetition_penalty": 1.05, | |
| "temperature": 0.7, | |
| "top_p": 0.8, | |
| "top_k": 20, | |
| "transformers_version": "4.37.0" | |
| } | |