Instructions to use PhilSad/phil-lora-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PhilSad/phil-lora-2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("PhilSad/phil-lora-2") prompt = "a photo of sks man" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download image_0.png from PhilSad/phil-lora-2: direct link, hf CLI and curl.
- Browser
- Download file 1.42 MB
-
https://huggingface.co/PhilSad/phil-lora-2/resolve/main/image_0.png
- Command line
-
hf download hf://PhilSad/phil-lora-2/image_0.png
-
curl -L -o image_0.png https://huggingface.co/PhilSad/phil-lora-2/resolve/main/image_0.png
1.42 MB

- Xet hash:
- 2c07779bbb78088b98c56964103ef0e0b1fd4531e9c30d891dfef8d464c60704
- Size of remote file:
- 1.42 MB
- SHA256:
- a33fc8ce1f45d9116d2f29349e285f0f75200057a58c5330fb34a7d1c9b90c81
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.