Instructions to use rag000/rag000dream3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rag000/rag000dream3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rag000/rag000dream3", 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 rag000/rag000dream3: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/rag000/rag000dream3/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://rag000/rag000dream3/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rag000/rag000dream3/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- ee7ef40c78a715fbd0ce23dc4d381b555ec45e79fbe269d8199c8c891b899d7f
- Size of remote file:
- 246 MB
- SHA256:
- 97474bcbabd268482953fa3c2312b82f7b460504b7fcec70f683256cc6649406
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