Instructions to use jpawan33/kag-sd-100-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jpawan33/kag-sd-100-model 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-2", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jpawan33/kag-sd-100-model") 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-2000/optimizer.bin from jpawan33/kag-sd-100-model: direct link, hf CLI and curl.
- Browser
- Download file 6.85 MB
-
https://huggingface.co/jpawan33/kag-sd-100-model/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://jpawan33/kag-sd-100-model/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/jpawan33/kag-sd-100-model/resolve/main/checkpoint-2000/optimizer.bin
6.85 MB
- Xet hash:
- 7daff726d8aa7dc2097c11ccd0edc9b76f85a4b77ab8ddca3677a102adb70bcb
- Size of remote file:
- 6.85 MB
- SHA256:
- 0cdc4961626e62fae0033f15326c85877780bc1a48b058d2223e94e5e45c5f3c
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