Instructions to use chaechae7/FLUX.2-dev-transformer-fp8only-scaled-runtime-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chaechae7/FLUX.2-dev-transformer-fp8only-scaled-runtime-v1 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("chaechae7/FLUX.2-dev-transformer-fp8only-scaled-runtime-v1", 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
| { | |
| "processor_class": "PixtralProcessor", | |
| "image_processor_type": "PixtralImageProcessor", | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "rescale_factor": 0.00392156862745098, | |
| "resample": 3, | |
| "size": { | |
| "longest_edge": 1540, | |
| "shortest_edge": 14 | |
| }, | |
| "patch_size": 14 | |
| } | |