Instructions to use mrinaldi86/dog_sks_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mrinaldi86/dog_sks_test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mrinaldi86/dog_sks_test", 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 mrinaldi86/dog_sks_test: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/mrinaldi86/dog_sks_test/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://mrinaldi86/dog_sks_test/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mrinaldi86/dog_sks_test/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- b8472f91f09d5b73c384d32ed8aa4d8cd0cf3bed860d5358e660cfaa3941ebc3
- Size of remote file:
- 492 MB
- SHA256:
- 5b429bae179aa92d6e7a91aff20d966c14120af72fe78e61df90c407e848526f
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