Instructions to use vvtq/model-lora-sd15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vvtq/model-lora-sd15 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("vvtq/model-lora-sd15") 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-2000/optimizer.bin from vvtq/model-lora-sd15: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/vvtq/model-lora-sd15/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://vvtq/model-lora-sd15/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/vvtq/model-lora-sd15/resolve/main/checkpoint-2000/optimizer.bin
6.59 MB
- Xet hash:
- 1c70ce771c2f15a23a2219f6fd752cc7dec7d1a3c3cd8b7d6b34691773d3acd8
- Size of remote file:
- 6.59 MB
- SHA256:
- aca9555d00367ff699beda814cec207a3924a180fea85b119424d93c43e48737
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