Instructions to use hf-internal-testing/lora_dreambooth_dog_example with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/lora_dreambooth_dog_example 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_dreambooth_dog_example") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-500/optimizer.bin from hf-internal-testing/lora_dreambooth_dog_example: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/hf-internal-testing/lora_dreambooth_dog_example/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://hf-internal-testing/lora_dreambooth_dog_example/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/hf-internal-testing/lora_dreambooth_dog_example/resolve/main/checkpoint-500/optimizer.bin
6.59 MB
- Xet hash:
- 5452b47fc925a0e023703550be28cc502c34e476d26f51530489a526d30d1ceb
- Size of remote file:
- 6.59 MB
- SHA256:
- 0df6d40f9a448f8e7e8aada0de194fe7de55b3f1a2547dfbec28c532c75add66
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.