Instructions to use SidXXD/m-651 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/m-651 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-651", 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-651: direct link, hf CLI and curl.
- Browser
- Download file 76.7 MB
-
https://huggingface.co/SidXXD/m-651/resolve/main/pytorch_custom_diffusion_weights.bin
- Command line
-
hf download hf://SidXXD/m-651/pytorch_custom_diffusion_weights.bin
-
curl -L -o pytorch_custom_diffusion_weights.bin https://huggingface.co/SidXXD/m-651/resolve/main/pytorch_custom_diffusion_weights.bin
76.7 MB
- Xet hash:
- abfb717ca43a96293684cb28cd553db2aec93ac11a4b3dc86de08dd54bf9ee91
- Size of remote file:
- 76.7 MB
- SHA256:
- 77f33da375b5876b8435ee6a90b593f83cf677a98251eeda6068c88b3c024b7d
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