Instructions to use SumDeed/sku_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SumDeed/sku_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("SumDeed/sku_output") prompt = "a golden oreo mini pack" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-600/optimizer.bin from SumDeed/sku_output: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/SumDeed/sku_output/resolve/main/checkpoint-600/optimizer.bin
- Command line
-
hf download hf://SumDeed/sku_output/checkpoint-600/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/SumDeed/sku_output/resolve/main/checkpoint-600/optimizer.bin
6.59 MB
- Xet hash:
- 51f61b4870ae097f7ae9446d1c32a87d16260d3cfd9a9b2e20a45105109a2154
- Size of remote file:
- 6.59 MB
- SHA256:
- fab1273aacbee56174e0210deeac533b8543677e10fb797b0437b48c2a03ea00
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