Instructions to use Boogu/Boogu-Image-0.1-Edit-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Boogu/Boogu-Image-0.1-Edit-fp8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Boogu/Boogu-Image-0.1-Edit-fp8", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download model_index.json from Boogu/Boogu-Image-0.1-Edit-fp8: direct link, hf CLI and curl.
- Browser
- Download file 501 Bytes
-
https://huggingface.co/Boogu/Boogu-Image-0.1-Edit-fp8/resolve/main/model_index.json
- Command line
-
hf download hf://Boogu/Boogu-Image-0.1-Edit-fp8/model_index.json
-
curl -L -o model_index.json https://huggingface.co/Boogu/Boogu-Image-0.1-Edit-fp8/resolve/main/model_index.json
501 Bytes
| { | |
| "_class_name": "BooguImagePipeline", | |
| "_diffusers_version": "0.35.2", | |
| "mllm": [ | |
| "transformers", | |
| "Qwen3VLForConditionalGeneration" | |
| ], | |
| "processor": [ | |
| "transformers", | |
| "Qwen3VLProcessor" | |
| ], | |
| "scheduler": [ | |
| "scheduling_flow_match_euler_discrete_time_shifting", | |
| "FlowMatchEulerDiscreteScheduler" | |
| ], | |
| "transformer": [ | |
| "boogu.models.transformers.transformer_boogu", | |
| "BooguImageTransformer2DModel" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ] | |
| } | |