Instructions to use gubaguba/borya2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gubaguba/borya2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gubaguba/borya2", 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 gubaguba/borya2: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/gubaguba/borya2/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://gubaguba/borya2@refs/pr/2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gubaguba/borya2/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 310899bdcbaa33f45e8c84d8d5ab55747b7e35bb0e86bc54bf4ec45e1ef82fb0
- Size of remote file:
- 246 MB
- SHA256:
- 7d2ab58df36f54d395a3f84d28065f8cd6c391670c4a5ff8053b2f73f38a1e06
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