Instructions to use Hemanth-thunder/stable_diffusion_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Hemanth-thunder/stable_diffusion_lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Hemanth-thunder/stable_diffusion_lora", dtype=torch.bfloat16, device_map="cuda") prompt = "hmat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| .PHONY: quality style test | |
| # Check that source code meets quality standards | |
| quality: | |
| black --check --line-length 119 --target-version py38 . | |
| isort --check-only . | |
| flake8 --max-line-length 119 | |
| # Format source code automatically | |
| style: | |
| black --line-length 119 --target-version py38 . | |
| isort . | |
| test: | |
| pytest -sv ./src/ | |
| docker: | |
| docker build -t autotrain-advanced:latest . | |
| docker tag autotrain-advanced:latest huggingface/autotrain-advanced:latest | |
| docker push huggingface/autotrain-advanced:latest | |
| pip: | |
| rm -rf build/ | |
| rm -rf dist/ | |
| python setup.py sdist bdist_wheel | |
| twine upload dist/* --verbose |