Tabular Classification
PyTorch
LiteRT
TF-Keras
ONNX
LiteRT
industrial
edge-ai
tensorflow
synthetic-data
Instructions to use sankalpsthakur/forge-tiny-drift-multiruntime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use sankalpsthakur/forge-tiny-drift-multiruntime with LiteRT:
# 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
File size: 998 Bytes
33355bf | 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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | [build-system]
requires = ["setuptools>=68"]
build-backend = "setuptools.build_meta"
[project]
name = "forge-industrial-agent-lab"
version = "0.2.0"
description = "Plant-safe multi-agent, PLC and edge time-series reference for Hugging Face Spaces"
readme = "README.md"
requires-python = ">=3.10"
license = {text = "Apache-2.0"}
authors = [{name = "Forge contributors"}]
dependencies = ["cryptography>=45", "numpy>=2,<3"]
[project.optional-dependencies]
demo = ["gradio>=5,<7"]
agents = ["smolagents>=1.20"]
edge = ["fastapi>=0.115", "uvicorn>=0.34"]
model-export = [
"ai-edge-litert>=2.1",
"numpy==2.5.1",
"torch==2.13.0",
"onnx>=1.22",
"onnxscript>=0.5",
"onnxruntime>=1.28",
"tensorflow-cpu>=2.21",
]
test = ["pytest>=8", "httpx2>=2.9"]
[tool.pytest.ini_options]
pythonpath = ["src"]
testpaths = ["tests"]
[tool.setuptools.packages.find]
where = ["src"]
[tool.ruff]
line-length = 100
exclude = [".venv", "upstream"]
[tool.ruff.lint]
select = ["B", "E", "F", "I", "RUF", "UP"]
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