Instructions to use Jianbiao/dreamforge-s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jianbiao/dreamforge-s with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Jianbiao/dreamforge-s", 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/diffusion_pytorch_model.bin from Jianbiao/dreamforge-s: direct link, hf CLI and curl.
- Browser
- Download file 1.46 GB
-
https://huggingface.co/Jianbiao/dreamforge-s/resolve/main/controlnet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Jianbiao/dreamforge-s/controlnet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Jianbiao/dreamforge-s/resolve/main/controlnet/diffusion_pytorch_model.bin
1.46 GB
- Xet hash:
- 221667f5113a1566bf1b5f737ef12765eb7286a6bab072ec7a68fb79fb27991b
- Size of remote file:
- 1.46 GB
- SHA256:
- 34524c766706dcac5a2316f8cd2b3b89dd85739b8823be3c5b19144f6223c4e3
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