Instructions to use lsmpp/kontextrefiner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lsmpp/kontextrefiner with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lsmpp/kontextrefiner", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| name: Benchmarking tests | |
| on: | |
| workflow_dispatch: | |
| schedule: | |
| - cron: "30 1 1,15 * *" # every 2 weeks on the 1st and the 15th of every month at 1:30 AM | |
| env: | |
| DIFFUSERS_IS_CI: yes | |
| HF_HUB_ENABLE_HF_TRANSFER: 1 | |
| HF_HOME: /mnt/cache | |
| OMP_NUM_THREADS: 8 | |
| MKL_NUM_THREADS: 8 | |
| BASE_PATH: benchmark_outputs | |
| jobs: | |
| torch_models_cuda_benchmark_tests: | |
| env: | |
| SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK_URL_BENCHMARK }} | |
| name: Torch Core Models CUDA Benchmarking Tests | |
| strategy: | |
| fail-fast: false | |
| max-parallel: 1 | |
| runs-on: | |
| group: aws-g6e-4xlarge | |
| container: | |
| image: diffusers/diffusers-pytorch-cuda | |
| options: --shm-size "16gb" --ipc host --gpus 0 | |
| steps: | |
| - name: Checkout diffusers | |
| uses: actions/checkout@v3 | |
| with: | |
| fetch-depth: 2 | |
| - name: NVIDIA-SMI | |
| run: | | |
| nvidia-smi | |
| - name: Install dependencies | |
| run: | | |
| apt update | |
| apt install -y libpq-dev postgresql-client | |
| python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH" | |
| python -m uv pip install -e [quality,test] | |
| python -m uv pip install -r benchmarks/requirements.txt | |
| - name: Environment | |
| run: | | |
| python utils/print_env.py | |
| - name: Diffusers Benchmarking | |
| env: | |
| HF_TOKEN: ${{ secrets.DIFFUSERS_HF_HUB_READ_TOKEN }} | |
| run: | | |
| cd benchmarks && python run_all.py | |
| - name: Push results to the Hub | |
| env: | |
| HF_TOKEN: ${{ secrets.DIFFUSERS_BOT_TOKEN }} | |
| run: | | |
| cd benchmarks && python push_results.py | |
| mkdir $BASE_PATH && cp *.csv $BASE_PATH | |
| - name: Test suite reports artifacts | |
| if: ${{ always() }} | |
| uses: actions/upload-artifact@v4 | |
| with: | |
| name: benchmark_test_reports | |
| path: benchmarks/${{ env.BASE_PATH }} | |
| # TODO: enable this once the connection problem has been resolved. | |
| - name: Update benchmarking results to DB | |
| env: | |
| PGDATABASE: metrics | |
| PGHOST: ${{ secrets.DIFFUSERS_BENCHMARKS_PGHOST }} | |
| PGUSER: transformers_benchmarks | |
| PGPASSWORD: ${{ secrets.DIFFUSERS_BENCHMARKS_PGPASSWORD }} | |
| BRANCH_NAME: ${{ github.head_ref || github.ref_name }} | |
| run: | | |
| git config --global --add safe.directory /__w/diffusers/diffusers | |
| commit_id=$GITHUB_SHA | |
| commit_msg=$(git show -s --format=%s "$commit_id" | cut -c1-70) | |
| cd benchmarks && python populate_into_db.py "$BRANCH_NAME" "$commit_id" "$commit_msg" | |
| - name: Report success status | |
| if: ${{ success() }} | |
| run: | | |
| pip install requests && python utils/notify_benchmarking_status.py --status=success | |
| - name: Report failure status | |
| if: ${{ failure() }} | |
| run: | | |
| pip install requests && python utils/notify_benchmarking_status.py --status=failure |