Instructions to use garg-aayush/clock with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use garg-aayush/clock 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-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("garg-aayush/clock") prompt = "A [V] clock on the beach" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-1000/optimizer.bin from garg-aayush/clock: direct link, hf CLI and curl.
- Browser
- Download file 744 MB
-
https://huggingface.co/garg-aayush/clock/resolve/main/checkpoint-1000/optimizer.bin
- Command line
-
hf download hf://garg-aayush/clock/checkpoint-1000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/garg-aayush/clock/resolve/main/checkpoint-1000/optimizer.bin
744 MB
- Xet hash:
- 420f36d5a0f71accaa1790335548011549b6a44966457d01dd1bafdb721cee33
- Size of remote file:
- 744 MB
- SHA256:
- 9933747b5cf6f80979189a6b15bc8551e2a1364511a4ed1f86d5cadd226afab6
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