Instructions to use jiangdaniel/dog_lora_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jiangdaniel/dog_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("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jiangdaniel/dog_lora_2") 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 jiangdaniel/dog_lora_2: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/jiangdaniel/dog_lora_2/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://jiangdaniel/dog_lora_2/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/jiangdaniel/dog_lora_2/resolve/main/checkpoint-500/optimizer.bin
6.59 MB
- Xet hash:
- 4d400005c0c2ca969c117ea5d711f6c5fedfcc9bf00b7cd666824af1fa966507
- Size of remote file:
- 6.59 MB
- SHA256:
- e7046190b8384340df75d0e9a8be6ced787e664b86fdc72c2974bbd229d8dc79
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