Instructions to use TheStageAI/Elastic-Z-Image-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TensorRT
How to use TheStageAI/Elastic-Z-Image-Turbo with TensorRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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---
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license: other
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license_name: thestage-ai-proprietary
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library_name: qlip
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tags:
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- tensorrt
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- qlip
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- thestage
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- diffusion
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- acceleration
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- lora
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---
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# Precompiled TensorRT Engines by Qlip
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Precompiled [Qlip](https://thestage.ai) engines for accelerated diffusion model inference. Base model weights are **not** included.
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For supported models, benchmarks, and usage instructions see [ComfyUI-Qlip](https://github.com/TheStageAI/ComfyUI-Qlip).
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## Usage
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### ComfyUI (automatic download)
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In the **Qlip Engines Loader** node, set the `hf_repo` input. Engines are downloaded once and cached locally.
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### Manual download
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```bash
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pip install huggingface-hub
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huggingface-cli download TheStageAI/<repo-name> \
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--local-dir ./engines \
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--include "models/H100/<variant>/*"
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```
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## Installation
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```bash
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# Qlip core
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pip install 'qlip.core[nvidia]' \
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--extra-index-url https://thestage.jfrog.io/artifactory/api/pypi/pypi-thestage-ai-production/simple
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# elastic_models (LoRA runtime support)
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pip install 'thestage-elastic-models[nvidia]' \
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--extra-index-url https://thestage.jfrog.io/artifactory/api/pypi/pypi-thestage-ai-production/simple
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```
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## Requirements
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- NVIDIA GPU with CUDA 12.x
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- TensorRT 10.13.3.9 (must match compilation version)
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- Engines are GPU-architecture specific — recompile after changing hardware
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## License
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Proprietary. Powered by [TheStage AI](https://thestage.ai).
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