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/hand_pose_model.pth from Akalabeth12/Text-to-Image: direct link, hf CLI and curl.
- Browser
- Download file 147 MB
-
https://huggingface.co/Akalabeth12/Text-to-Image/resolve/main/CONTROLNET/hand_pose_model.pth
- Command line
-
hf download hf://Akalabeth12/Text-to-Image/CONTROLNET/hand_pose_model.pth
-
curl -L -o hand_pose_model.pth https://huggingface.co/Akalabeth12/Text-to-Image/resolve/main/CONTROLNET/hand_pose_model.pth
147 MB
- Xet hash:
- a47656d809c196589440a53214c1c961e6034446023b38404ad45e0e97b3fd1b
- Size of remote file:
- 147 MB
- SHA256:
- b76b00d1750901abd07b9f9d8c98cc3385b8fe834a26d4b4f0aad439e75fc600
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