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/facenet.pth from Akalabeth12/Text-to-Image: direct link, hf CLI and curl.
- Browser
- Download file 154 MB
-
https://huggingface.co/Akalabeth12/Text-to-Image/resolve/main/CONTROLNET/facenet.pth
- Command line
-
hf download hf://Akalabeth12/Text-to-Image/CONTROLNET/facenet.pth
-
curl -L -o facenet.pth https://huggingface.co/Akalabeth12/Text-to-Image/resolve/main/CONTROLNET/facenet.pth
154 MB
- Xet hash:
- 834cd62067b584a16d83030398da6af1c242d03b6ec5ad99a190ed583ff85e1c
- Size of remote file:
- 154 MB
- SHA256:
- 8beb52e548624ffcc4aed12af7aee7dcbfaeea420c75609fee999fe7add79d43
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