Instructions to use PoolerSP/LogiLeteV1_inpaint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PoolerSP/LogiLeteV1_inpaint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("PoolerSP/LogiLeteV1_inpaint", 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 unet/diffusion_pytorch_model.bin from PoolerSP/LogiLeteV1_inpaint: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/PoolerSP/LogiLeteV1_inpaint/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://PoolerSP/LogiLeteV1_inpaint/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/PoolerSP/LogiLeteV1_inpaint/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 268ff2c026b59b6a7ed693410b1b022f40e26c727ebbefa1869b73f17330ce0a
- Size of remote file:
- 3.44 GB
- SHA256:
- f7a45dfcb69126a90202131e58c9ae6de5ef98e5bd26b617fd88e2d7d0c11ce5
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