Instructions to use reeen115/lora_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use reeen115/lora_output 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-2-1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("reeen115/lora_output") prompt = "cardboards, grayscale" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-100/optimizer.bin from reeen115/lora_output: direct link, hf CLI and curl.
- Browser
- Download file 6.85 MB
-
https://huggingface.co/reeen115/lora_output/resolve/main/checkpoint-100/optimizer.bin
- Command line
-
hf download hf://reeen115/lora_output/checkpoint-100/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/reeen115/lora_output/resolve/main/checkpoint-100/optimizer.bin
6.85 MB
- Xet hash:
- e672914129896583e874a48cf767778f74f73d9afb6e80504d9ea9e120c94afb
- Size of remote file:
- 6.85 MB
- SHA256:
- 4600177fa9062d39d658f8b54d4cd6f166e35673d40aa71eb2da2743faca1e2a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.