Instructions to use limingcv/InstructDiffusion_diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use limingcv/InstructDiffusion_diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("limingcv/InstructDiffusion_diffusers", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vae/diffusion_pytorch_model.safetensors from limingcv/InstructDiffusion_diffusers: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/limingcv/InstructDiffusion_diffusers/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://limingcv/InstructDiffusion_diffusers/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/limingcv/InstructDiffusion_diffusers/resolve/main/vae/diffusion_pytorch_model.safetensors
335 MB
- Xet hash:
- 4426079187445eb8dc8a8327a7b5699b8b3e77b2e982a083266ba200def74377
- Size of remote file:
- 335 MB
- SHA256:
- c365a5261aaffe9d7646e3ee9ba096b70bed46408035784b3ea487bc2375599c
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