Instructions to use medmac01/miathon-controlNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use medmac01/miathon-controlNet with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("medmac01/miathon-controlNet", 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/pytorch_model.bin from medmac01/miathon-controlNet: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/medmac01/miathon-controlNet/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://medmac01/miathon-controlNet/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/medmac01/miathon-controlNet/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 4ebb0796badedb3e2fc15ac5852ac99e77aff5c406547dbc85c330a947ab29ea
- Size of remote file:
- 246 MB
- SHA256:
- 4b576abd5b3f4e92b2721b2f3ff5e0a7ec22c0bc1131224b5859659e21471857
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.