Currently, running some pickle files trained on Aliro necessitates Python version 3.7.16 and sklearn version 0.24.2. Users will encounter issues testing models if their sklearn version is incompatible with the version in which the model's pickle file was created.
We provide the Colab script tailored for collaborators, such as doctors and nurses, enabling them to load pickle files from Aliro and test them on a testing set without the need for environment configuration. However, for example, specific model, like the GradientBoostingClassifier generate error messages due to sklearn version mismatches.
My solution employs the Aliro machine Docker container for loading pickle files trained on Aliro. Since this container is equipped with Python version 3.7.16 and sklearn version 0.24.2, it facilitates seamless pickle file loading and model testing. Nonetheless, this approach may prove challenging for users without development experience to utilize and follow.
Currently, running some pickle files trained on Aliro necessitates Python version 3.7.16 and sklearn version 0.24.2. Users will encounter issues testing models if their sklearn version is incompatible with the version in which the model's pickle file was created.
We provide the Colab script tailored for collaborators, such as doctors and nurses, enabling them to load pickle files from Aliro and test them on a testing set without the need for environment configuration. However, for example, specific model, like the GradientBoostingClassifier generate error messages due to sklearn version mismatches.
My solution employs the Aliro machine Docker container for loading pickle files trained on Aliro. Since this container is equipped with Python version 3.7.16 and sklearn version 0.24.2, it facilitates seamless pickle file loading and model testing. Nonetheless, this approach may prove challenging for users without development experience to utilize and follow.