Scikit-Learn runtime for MLServer
This package provides a MLServer runtime compatible with Scikit-Learn.
Usage
You can install the runtime, alongside mlserver, as:
pip install mlserver mlserver-sklearn
For further information on how to use MLServer with Scikit-Learn, you can check out this worked out example.
Content Types
If no content type is present on the request or metadata, the Scikit-Learn runtime will try to decode the payload as a NumPy Array. To avoid this, either send a different content type explicitly, or define the correct one as part of your model's metadata.
Model Outputs
The Scikit-Learn inference runtime exposes a number of outputs depending on the
model type.
These outputs match to the predict, predict_proba and transform methods
of the Scikit-Learn model.
| Output | Returned By Default | Availability |
|---|---|---|
predict |
✅ | Available on most models, but not in Scikit-Learn pipelines. |
predict_proba |
❌ | Only available on non-regressor models. |
transform |
❌ | Only available on Scikit-Learn pipelines. |
By default, the runtime will only return the output of predict.
However, you are able to control which outputs you want back through the
outputs field of your {class}InferenceRequest <mlserver.types.InferenceRequest> payload.
For example, to only return the model's predict_proba output, you could
define a payload such as:
---
emphasize-lines: 10-12
---
{
"inputs": [
{
"name": "my-input",
"datatype": "INT32",
"shape": [2, 2],
"data": [1, 2, 3, 4]
}
],
"outputs": [
{ "name": "predict_proba" }
]
}
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Release files for mlserver-sklearn 1.7.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mlserver_sklearn-1.7.1.tar.gz | 6.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mlserver_sklearn-1.7.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 14.9 kB
Release files / mlserver_sklearn-1.7.1.tar.gz
| Download URL | mlserver_sklearn-1.7.1.tar.gz |
|---|---|
| Size | 6.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / mlserver_sklearn-1.7.1-py3-none-any.whl
| Download URL | mlserver_sklearn-1.7.1-py3-none-any.whl |
|---|---|
| Size | 8.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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| Uploaded via |
poetry/2.1.3 CPython/3.10.17 Linux/6.11.0-1015-azure
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