Instructions to use Yastreb/anilin123 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yastreb/anilin123 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yastreb/anilin123", 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 Yastreb/anilin123: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/Yastreb/anilin123/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Yastreb/anilin123/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Yastreb/anilin123/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 503860be65fa8c809b26a97885012b15adeec4858c97673144ff24b6a8313d63
- Size of remote file:
- 246 MB
- SHA256:
- d8ad5faa2ae30a0ec44a6960b485f471eacb9e5db2c2234798f86714ba583027
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