Instructions to use MarcosRodrigo/lep-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MarcosRodrigo/lep-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("MarcosRodrigo/lep-model") prompt = "a photo of lep" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-1000/optimizer.bin from MarcosRodrigo/lep-model: direct link, hf CLI and curl.
- Browser
- Download file 444 MB
-
https://huggingface.co/MarcosRodrigo/lep-model/resolve/main/checkpoint-1000/optimizer.bin
- Command line
-
hf download hf://MarcosRodrigo/lep-model/checkpoint-1000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/MarcosRodrigo/lep-model/resolve/main/checkpoint-1000/optimizer.bin
444 MB
- Xet hash:
- 420f73e1d20adf405a8130c06dffd69bad7b3fee7433b94b522d43c153c098ca
- Size of remote file:
- 444 MB
- SHA256:
- e22430a9d8535d2498a8450a1b10789f2e08c7ed55b40d5c6f87a650bc211836
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.