Instructions to use ModelsLab/blipdiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ModelsLab/blipdiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ModelsLab/blipdiffusion", 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.safetensors from ModelsLab/blipdiffusion: direct link, hf CLI and curl.
- Browser
- Download file 1.45 GB
-
https://huggingface.co/ModelsLab/blipdiffusion/resolve/main/controlnet/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://ModelsLab/blipdiffusion/controlnet/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/ModelsLab/blipdiffusion/resolve/main/controlnet/diffusion_pytorch_model.safetensors
1.45 GB
- Xet hash:
- a34e77b7357e5afddf5e2aa761deeaad9bccfabfe908b4d02620c689b3a34b38
- Size of remote file:
- 1.45 GB
- SHA256:
- e19821a00e6d1817b37286a21d5c4f8915076949b0e81846c4f92c96ffb46db7
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