Instructions to use c-eshih/human_stable_diffusion_mask_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use c-eshih/human_stable_diffusion_mask_2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("c-eshih/human_stable_diffusion_mask_2", 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 checkpoint-6800/optimizer.bin from c-eshih/human_stable_diffusion_mask_2: direct link, hf CLI and curl.
- Browser
- Download file 6.88 GB
-
https://huggingface.co/c-eshih/human_stable_diffusion_mask_2/resolve/main/checkpoint-6800/optimizer.bin
- Command line
-
hf download hf://c-eshih/human_stable_diffusion_mask_2/checkpoint-6800/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/c-eshih/human_stable_diffusion_mask_2/resolve/main/checkpoint-6800/optimizer.bin
6.88 GB
- Xet hash:
- b62cb73420739a1f911a77dafbf34e1ab14628b8e478fc71083e280f6f5ecd3f
- Size of remote file:
- 6.88 GB
- SHA256:
- b88f2c004038798c03fc6a3c7393e2fc697ed82995aa8f2db5f0d931342bad41
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