Instructions to use jyp96/dog2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jyp96/dog2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jyp96/dog2") prompt = "A photo of sks dog2 in a bucket" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-200/optimizer.bin from jyp96/dog2: direct link, hf CLI and curl.
- Browser
- Download file 19.1 MB
-
https://huggingface.co/jyp96/dog2/resolve/main/checkpoint-200/optimizer.bin
- Command line
-
hf download hf://jyp96/dog2/checkpoint-200/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/jyp96/dog2/resolve/main/checkpoint-200/optimizer.bin
19.1 MB
- Xet hash:
- 364b109d2e48552851f299393a1bf6398b45e70e687fbf58a1ff5c4c15c5c726
- Size of remote file:
- 19.1 MB
- SHA256:
- 750fd1571639cbec2de2adc236d0075edcd2f57aa49cd8b8aa9e4227f5e41c1c
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