Instructions to use Harahan/MeanFlowNFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Harahan/MeanFlowNFT with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3.5-medium", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Harahan/MeanFlowNFT") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- f15938d028360b1aa31f2f21b735adff27c8ddf2a29f345b87f6077bfb1f10eb
- Size of remote file:
- 146 kB
- SHA256:
- 6f7c6d7ea57b23e744dbb36c403190da3cf246e2c5d540ec76e7cb764ba0da5b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.