Instructions to use Intel/GLM-Image-int4-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Intel/GLM-Image-int4-AutoRound with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Intel/GLM-Image-int4-AutoRound", 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 Intel/GLM-Image-int4-AutoRound: direct link, hf CLI and curl.
- Browser
- Download file 812 MB
-
https://huggingface.co/Intel/GLM-Image-int4-AutoRound/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://Intel/GLM-Image-int4-AutoRound/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/Intel/GLM-Image-int4-AutoRound/resolve/main/vae/diffusion_pytorch_model.safetensors
812 MB
- Xet hash:
- e9982eec19bedfefa9162f6fd91fc210e05ed0079ddbbed78a99c50d157eb3b0
- Size of remote file:
- 812 MB
- SHA256:
- a80a129b649cdb6d74d9c2b5bb060f3b882b7826b63a732306a7d3393deedbc0
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