Instructions to use fghjfbrtb/wr1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fghjfbrtb/wr1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fghjfbrtb/wr1", 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 fghjfbrtb/wr1: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/fghjfbrtb/wr1/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://fghjfbrtb/wr1/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fghjfbrtb/wr1/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 7e93491b5371715f4ecf980037037cdbb87e67af80d140da49d8cbbc571805b1
- Size of remote file:
- 246 MB
- SHA256:
- 1347f8c1d3056dad1d23530837a7655e441cf5e2464dbc02d9ace4fbf2f0b305
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