Instructions to use jqsl2012/test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jqsl2012/test_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jqsl2012/test_model", 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 unet/diffusion_pytorch_model.bin from jqsl2012/test_model: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/jqsl2012/test_model/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://jqsl2012/test_model/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/jqsl2012/test_model/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- eaebd826e36e125e64f8da2bbc4b7198339be9a63aab2a60640887cd33bf89bb
- Size of remote file:
- 3.44 GB
- SHA256:
- ea6712253fb21299b447b171bcbe80c373e031b862aecc73b59d2f8bf09f598f
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