Instructions to use flax/mo-di-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use flax/mo-di-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("flax/mo-di-diffusion", dtype=torch.bfloat16, device_map="cuda") 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
Download text_encoder/flax_model.msgpack from flax/mo-di-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/flax/mo-di-diffusion/resolve/main/text_encoder/flax_model.msgpack
- Command line
-
hf download hf://flax/mo-di-diffusion/text_encoder/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/flax/mo-di-diffusion/resolve/main/text_encoder/flax_model.msgpack
492 MB
- Xet hash:
- ca5b10873ef805c13d17dad3a156eb8d11312ca37e1499a03086b583a67c891d
- Size of remote file:
- 492 MB
- SHA256:
- a6a775e2bfffd035fdf756972c536c260050300e6247d749b148a072507ce6e7
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