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-300/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-300/optimizer.bin
- Command line
-
hf download hf://jiangdaniel/dog_lora_2/checkpoint-300/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/jiangdaniel/dog_lora_2/resolve/main/checkpoint-300/optimizer.bin
6.59 MB
- Xet hash:
- 76fb784eea41218d2cc1b0a4fc25a21da8c52e60203a2507e918ba1c43a562fd
- Size of remote file:
- 6.59 MB
- SHA256:
- 22774f54f22f738add6680e462cb8a33a35d0768797080a7a21960a80ae14d1e
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