soyml
soyml: framework-independent ML model inference
soy - a prefix indicating that this is a subpar substitute for the real thing :)
pitch
machine learning models are often trained in one framework (e.g. pytorch) and deployed in another. there are many different inference-focused frameworks, but they all have different APIs. this makes it difficult to deploy models in a framework-agnostic way. soyml aims to solve this problem by providing a simple, framework-agnostic API for inference, abstracting away the details of the underlying framework, and just letting you turn inputs to outputs and nothing else.
features
currently supported backends:
- pytorch (
torch) - onnxruntime (
ort) - wonnx (
wonnx) - ncnn (
ncnn)
1 maintainer
Metadata
1 maintainer
Release files for soyml 0.3.1
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| soyml-0.3.1.tar.gz | 5.4 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| soyml-0.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 13.3 kB
Release files / soyml-0.3.1.tar.gz
| Download URL | soyml-0.3.1.tar.gz |
|---|---|
| Size | 5.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.2.1 CPython/3.14.1 Darwin/24.6.0
|
Release files / soyml-0.3.1-py3-none-any.whl
| Download URL | soyml-0.3.1-py3-none-any.whl |
|---|---|
| Size | 7.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.2.1 CPython/3.14.1 Darwin/24.6.0
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Security for soyml 0.3.1
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