Instructions to use adammoss/cmd_f4_d8_128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use adammoss/cmd_f4_d8_128 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("adammoss/cmd_f4_d8_128", 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 diffusion_pytorch_model.bin from adammoss/cmd_f4_d8_128: direct link, hf CLI and curl.
- Browser
- Download file 222 MB
-
https://huggingface.co/adammoss/cmd_f4_d8_128/resolve/main/diffusion_pytorch_model.bin
- Command line
-
hf download hf://adammoss/cmd_f4_d8_128/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/adammoss/cmd_f4_d8_128/resolve/main/diffusion_pytorch_model.bin
222 MB
- Xet hash:
- cfac50b7913e7393e72d8096a6675e0f0030730aa8d4ad1649d0ae902f10e60c
- Size of remote file:
- 222 MB
- SHA256:
- ceb52b9e1edc1f6ff4d0b7e2ba18573a010c56742e69e43be75a36ea998ec4af
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