Instructions to use hf-internal-testing/lora-trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/lora-trained with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("hf-internal-testing/lora-trained") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-400/optimizer.bin from hf-internal-testing/lora-trained: direct link, hf CLI and curl.
- Browser
- Download file 9.03 MB
-
https://huggingface.co/hf-internal-testing/lora-trained/resolve/main/checkpoint-400/optimizer.bin
- Command line
-
hf download hf://hf-internal-testing/lora-trained/checkpoint-400/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/hf-internal-testing/lora-trained/resolve/main/checkpoint-400/optimizer.bin
9.03 MB
- Xet hash:
- 26aae408e625ef1eacd696f64e9a24e6daa67646449b8c2b510a150115d11170
- Size of remote file:
- 9.03 MB
- SHA256:
- d2ff4b87a7d2f97693ada375f68ef780ee4acaf6f4432b2d252459fa4d843591
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