Instructions to use codemanCheng/lora-trained-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codemanCheng/lora-trained-xl 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("codemanCheng/lora-trained-xl") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-500/optimizer.bin from codemanCheng/lora-trained-xl: direct link, hf CLI and curl.
- Browser
- Download file 47.4 MB
-
https://huggingface.co/codemanCheng/lora-trained-xl/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://codemanCheng/lora-trained-xl/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/codemanCheng/lora-trained-xl/resolve/main/checkpoint-500/optimizer.bin
47.4 MB
- Xet hash:
- dd07a89e75d887078c1ab896130522d6f00dbeaf7b99b5329b4e1f1074f303e4
- Size of remote file:
- 47.4 MB
- SHA256:
- b927b0cdcb48304a7f72d61a2ca4d094727abb237e46c5261cbf9a63e1bffe00
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