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Version: Cloud

Supported Versions

This article describes the supported versions and compatibility with supported ML frameworks. For some frameworks, links to example repositories on Gitlab are included. These example repositories can be used to create example deployments on Deeploy.

Deeploy1.29.x - 1.31.x1.32.x +
KServe0.9.00.11.0
Python3.7 - 3.93.8 - 3.11

Model Frameworks

The versions described in the following sections are the recommended versions on which the model images have been built. If you deviate from the version, check for potential compatibility issues.

PyTorch

Pytorch default imagepytorch/torchserve-kfs:0.6.0pytorch/torchserve-kfs:0.8.0
torch1.7.12.0.0
torchserve0.7.00.8.0
torch-model-archiver0.7.00.8.0

Tensorflow

Tensorflow default imagetensorflow/serving:2.6.2tensorflow/serving:2.6.2
tensorflow2.6.22.6.2

XGBoost

XGBoost default imagekserve/xgbserver:v0.9.0kserve/xgbserver:v0.11.0
xgboost1.5.01.7.5

Scikit-learn

Scikit-learn default imagekserve/sklearnserver:v0.9.0kserve/sklearnserver:v0.11.0
scikit-learn1.0.11.3.0
joblib1.1.01.3.1

LightGBM

LightGBM default imagekserve/lgbserver:v0.9.0kserve/lgbserver:v0.11.0
lightgbm3.3.23.3.5

Custom model Docker images

Deeploy versionEnterprise < v1.32.0Cloud & Enterprise >= v1.32.0
deeploy-cli-> 1.35.0
kserve0.9.00.11.0

Standard Explainers

Tree SHAP

Deploy a tree SHAP explainer without training it yourself. Available only for tree-based classification models when using XGBoost, Scikit-learn, or LightGBM model frameworks.

Saliency

Deploy a saliency based explainer without training it yourself. Available only for text generation and text-to-text generation models when using huggingface model framework.

Attention

Deploy a attention based explainer without training it yourself. Available only for text generation and text-to-text generation models when using huggingface model framework.

Trained Explainer Frameworks

The versions described in the following sections are the recommended versions for the specific frameworks to use. If you deviate from the version, check for potential compatibility issues.

Shap

Deeploy versionEnterprise < v1.32.0Cloud & Enterprise >= v1.32.0
shap0.36.00.42.1
dill0.3.30.3.7

Anchors

Deeploy versionEnterprise < v1.32.0Cloud & Enterprise >= v1.32.0
alibi0.6.40.9.4
dill0.3.30.3.7

MACE

Deeploy versionEnterprise < v1.32.0Cloud & Enterprise >= v1.32.0
omnixai1.1.41.3.1
dill0.3.30.3.7

PDP

  • Expected pre-trained explainer artefact: dill (explainer.dill)
Deeploy versionEnterprise < v1.32.0Cloud & Enterprise >= v1.32.0
omnixai1.1.41.3.1
dill0.3.30.3.7

Custom explainer Docker images

Deeploy versionEnterprise < v1.32.0Cloud & Enterprise >= v1.32.0
deeploy-cli-> 1.35.0
kserve0.9.00.11.0

Transformer Frameworks

Custom transformer Docker images

Deeploy versionEnterprise < v1.32.0Cloud & Enterprise >= v1.32.0
deeploy-cli->= 1.35.0
kserve0.9.00.11.0