Instructions to use jtwinfree44/cleed221 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jtwinfree44/cleed221 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jtwinfree44/cleed221", 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 jtwinfree44/cleed221: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/jtwinfree44/cleed221/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://jtwinfree44/cleed221/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jtwinfree44/cleed221/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- cdda784113c5f3cd71fdaad14275cfecd2ed870a0e232e940280fcd822a5a6f8
- Size of remote file:
- 246 MB
- SHA256:
- 5e0d73d7ab30ce524f8cc3a0e6054e3b910a506248c53de31fcd009d203bc43d
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