Instructions to use swapnabyna/OUTPUT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use swapnabyna/OUTPUT 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("swapnabyna/OUTPUT") 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 swapnabyna/OUTPUT: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/swapnabyna/OUTPUT/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://swapnabyna/OUTPUT/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/swapnabyna/OUTPUT/resolve/main/checkpoint-500/optimizer.bin
6.59 MB
- Xet hash:
- f103252739f902f8fb419a1f2e8ce95845b4b766cea5e4d38474d9c45f5d3542
- Size of remote file:
- 6.59 MB
- SHA256:
- c1f2b2d1cc8d7fcf59242aff9b975d50109f0c95fb168073ddf4c1b20816bf7f
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