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 Settings
- Draw Things
- DiffusionBee
File size: 605 Bytes
c0551d3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | .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 |