Instructions to use stablediffusionapi/vranipic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/vranipic 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/vranipic", 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 stablediffusionapi/vranipic: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/stablediffusionapi/vranipic/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://stablediffusionapi/vranipic/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/stablediffusionapi/vranipic/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 347b37169d730769acef286414b075d9ce5236854c6c8d5c1f8618e58f10d881
- Size of remote file:
- 246 MB
- SHA256:
- 3178c21d888d7b6e236134a2734970890a36700fc14c0392c50b9953fff96465
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