Instructions to use jafetsierra/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jafetsierra/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("jafetsierra/output") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-3/optimizer.bin from jafetsierra/output: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/jafetsierra/output/resolve/main/checkpoint-3/optimizer.bin
- Command line
-
hf download hf://jafetsierra/output/checkpoint-3/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/jafetsierra/output/resolve/main/checkpoint-3/optimizer.bin
6.59 MB
- Xet hash:
- 4c47831ca2f7e80172ecf817a54a49b1f580c3b57d63205b10f63d0329147991
- Size of remote file:
- 6.59 MB
- SHA256:
- 816845f8c8696a604bdff66082d4f85d576579e8565e354ba5e8a265d0fc7da5
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