Instructions to use dhanushreddy29/LOFIv3Inpaint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dhanushreddy29/LOFIv3Inpaint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dhanushreddy29/LOFIv3Inpaint", 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 dhanushreddy29/LOFIv3Inpaint: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/dhanushreddy29/LOFIv3Inpaint/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://dhanushreddy29/LOFIv3Inpaint/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dhanushreddy29/LOFIv3Inpaint/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 1f9437b2e8e0cabd4fef82c100bfea450a21e31cd052cb7534816da4315e9e70
- Size of remote file:
- 492 MB
- SHA256:
- 6be4cf2c6919ae4492e6e5e6044106555a5ca8689fd460709c580415d0b109bd
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