Instructions to use SidXXD/m-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/m-1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/m-1", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <v1*> person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download pytorch_custom_diffusion_weights.bin from SidXXD/m-1: direct link, hf CLI and curl.
- Browser
- Download file 76.7 MB
-
https://huggingface.co/SidXXD/m-1/resolve/main/pytorch_custom_diffusion_weights.bin
- Command line
-
hf download hf://SidXXD/m-1/pytorch_custom_diffusion_weights.bin
-
curl -L -o pytorch_custom_diffusion_weights.bin https://huggingface.co/SidXXD/m-1/resolve/main/pytorch_custom_diffusion_weights.bin
76.7 MB
- Xet hash:
- 0ae2ff3572e6eeee812bdc14db31917d9c8b938aa593a7d2a668bd0185e7e969
- Size of remote file:
- 76.7 MB
- SHA256:
- 89461fb6923892faff35eee12934fa43f9d9acb8eed073506412579c5216419d
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