Instructions to use princepride/daVinci-MagiHuman with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use princepride/daVinci-MagiHuman with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("princepride/daVinci-MagiHuman", 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 text_encoder/tokenizer.json from princepride/daVinci-MagiHuman: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/princepride/daVinci-MagiHuman/resolve/main/text_encoder/tokenizer.json
- Command line
-
hf download hf://princepride/daVinci-MagiHuman/text_encoder/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/princepride/daVinci-MagiHuman/resolve/main/text_encoder/tokenizer.json
34.4 MB
- Xet hash:
- 0d4b2ece5256e1747b6af78855154781f668db653056a61b1f5d4701bb47f248
- Size of remote file:
- 34.4 MB
- SHA256:
- 7794135caa3ea73918949c902a781cc61dab674a4b59c17d85931c77c1114cbd
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