Instructions to use gdelatournelle/laya-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Laya
How to use gdelatournelle/laya-onnx with Laya:
# 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
Download pyproject.toml from gdelatournelle/laya-onnx: direct link, hf CLI and curl.
- Browser
- Download file 1.02 kB
-
https://huggingface.co/gdelatournelle/laya-onnx/resolve/main/pyproject.toml
- Command line
-
hf download hf://gdelatournelle/laya-onnx/pyproject.toml
-
curl -L -o pyproject.toml https://huggingface.co/gdelatournelle/laya-onnx/resolve/main/pyproject.toml
1.02 kB
| [build-system] | |
| requires = ["hatchling"] | |
| build-backend = "hatchling.build" | |
| [project] | |
| name = "laya-onnx" | |
| version = "0.1.0" | |
| description = "ONNX Runtime inference for Laya typed decision models (CPU, OpenVINO, CUDA)" | |
| readme = "README.md" | |
| requires-python = ">=3.11" | |
| license = "Apache-2.0" | |
| dependencies = [ | |
| "onnxruntime>=1.18", | |
| "onnx>=1.16", | |
| "numpy>=1.26", | |
| "huggingface-hub>=0.34,<2", | |
| "tokenizers>=0.21,<1", | |
| ] | |
| [project.optional-dependencies] | |
| openvino = ["onnxruntime-openvino>=1.18"] | |
| gpu = ["onnxruntime-gpu>=1.18"] | |
| export = ["torch>=2.4", "transformers>=4.44", "safetensors>=0.4"] | |
| dev = ["pytest>=8", "ruff>=0.12", "build>=1"] | |
| demo = ["rich>=13,<16", "Pillow>=10"] | |
| ultrafast = ["playwright>=1.47"] | |
| [project.scripts] | |
| laya-onnx = "laya_onnx.cli:main" | |
| laya-onnx-snake = "laya_onnx.snake.cli:main" | |
| laya-onnx-ultrafast = "laya_onnx.ultrafast.cli:main" | |
| [project.urls] | |
| Repository = "https://github.com/Geoking2104/laya-onnx" | |
| [tool.hatch.build.targets.wheel] | |
| packages = ["laya_onnx"] | |