Instructions to use jschoormans/rvision_inp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jschoormans/rvision_inp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jschoormans/rvision_inp", 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 jschoormans/rvision_inp: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/jschoormans/rvision_inp/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://jschoormans/rvision_inp/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jschoormans/rvision_inp/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- d9c82e8cc6d1e77c3528ae7dc17a508cb11e94e8bf11291621f1d0f45f8c4a8a
- Size of remote file:
- 492 MB
- SHA256:
- 685f4a79ed75221910f1b8ba04beabbb5770e6b315e4ca76b4d32a241404c295
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