Instructions to use stablediffusionapi/baka2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/baka2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/baka2", 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 unet/diffusion_pytorch_model.bin from stablediffusionapi/baka2: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/stablediffusionapi/baka2/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://stablediffusionapi/baka2/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/stablediffusionapi/baka2/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 217f9978f5650f5dafbc06156a70e080c2d5bee6d1a61d15a7ecf3d50c42a438
- Size of remote file:
- 3.44 GB
- SHA256:
- 7b22ca6f8c3c408eb7defd60ffbdc791820cb4cba1a84db03aa63097f5c19401
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