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: 1,002 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 44 45 46 47 | {
"model_version": "forge-tiny-drift-v0.1",
"input": {
"name": "telemetry",
"shape": [
"batch",
50,
2
],
"dtype": "float32"
},
"channels": [
"peak_force_kn",
"part_deviation_mm"
],
"outputs": [
"probability"
],
"runtimes": [
"numpy",
"pytorch",
"onnxruntime",
"tensorflow",
"litert"
],
"framework_versions": {
"python": "3.12.13",
"numpy": "2.5.1",
"pytorch": "2.13.0+cu130",
"pytorch_cuda_build": "13.0",
"onnx": "1.22.0",
"onnxruntime": "1.28.0",
"tensorflow": "2.21.0",
"litert": "2.1.6"
},
"metrics": {
"synthetic_examples": 2048,
"accuracy": 0.987305,
"false_positive_rate": 0.014886,
"false_negative_rate": 0.009934,
"training_seed": 17
},
"data": "deterministic synthetic telemetry; no plant data",
"safety": "L0 decision support only; output cannot actuate equipment",
"cuda_validation": "not executed; no GPU or nvcc in the build workspace"
}
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