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
| { | |
| "text_encoder": { | |
| "mode": "copied_unchanged" | |
| }, | |
| "transformer": { | |
| "num_shards": 7, | |
| "num_output_entries": 534, | |
| "num_fp8_quantized": 203, | |
| "num_weight_scales_added": 203, | |
| "num_non_fp8_copied": 128, | |
| "total_size": 32231164544 | |
| } | |
| } | |