Instructions to use WALIDALI/joejordly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WALIDALI/joejordly with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WALIDALI/joejordly", 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 text_encoder/pytorch_model.bin from WALIDALI/joejordly: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/WALIDALI/joejordly/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://WALIDALI/joejordly/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/WALIDALI/joejordly/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- a5ccc9a542b9e5d67f68293ff939496f967580246d90d00f4664b2877859d601
- Size of remote file:
- 246 MB
- SHA256:
- bee74d974c1dbc66b397301772efea27a971d36f499ea6393ff7e7325e712fca
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