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-4/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-4/optimizer.bin
- Command line
-
hf download hf://jafetsierra/output/checkpoint-4/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/jafetsierra/output/resolve/main/checkpoint-4/optimizer.bin
6.59 MB
- Xet hash:
- ec928503713abcdf65d826d064e90420e4da633569d18928e58cb6472f8905b2
- Size of remote file:
- 6.59 MB
- SHA256:
- bba73b0c01ef226a857eb390b6193fefc8ec35329ddff2044e3a1ac21fcab0da
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