Instructions to use dde/js2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dde/js2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dde/js2", 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/model.safetensors from dde/js2: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/dde/js2/resolve/main/text_encoder/model.safetensors
- Command line
-
hf download hf://dde/js2/text_encoder/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/dde/js2/resolve/main/text_encoder/model.safetensors
492 MB
- Xet hash:
- 8873f80f68e346b8bc0d7eb16221113973f1dc7d480068f7e5b0df77bf084745
- Size of remote file:
- 492 MB
- SHA256:
- 4a2ba0c1c6f053271563f261b64a30c630bfe9bd1eba85b936cd6d84cee137de
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