Instructions to use Akalabeth12/Text-to-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Akalabeth12/Text-to-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Akalabeth12/Text-to-Image", 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
Download CONTROLNET/body_pose_model.pth from Akalabeth12/Text-to-Image: direct link, hf CLI and curl.
- Browser
- Download file 209 MB
-
https://huggingface.co/Akalabeth12/Text-to-Image/resolve/main/CONTROLNET/body_pose_model.pth
- Command line
-
hf download hf://Akalabeth12/Text-to-Image/CONTROLNET/body_pose_model.pth
-
curl -L -o body_pose_model.pth https://huggingface.co/Akalabeth12/Text-to-Image/resolve/main/CONTROLNET/body_pose_model.pth
209 MB
- Xet hash:
- c9051666fc983c2dc5f702827cb6bd07dbeb3d92da2ae13de69d5aefce9eb36f
- Size of remote file:
- 209 MB
- SHA256:
- 25a948c16078b0f08e236bda51a385d855ef4c153598947c28c0d47ed94bb746
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