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License: MIT License
PyMilo: Python for ML I/O
License: MIT License
Serialization for numpy.intc
data structure should be added(it is used in scikit svm models)
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Support WebSocket protocol to allow the exported models to be used in model streaming
Add symmetric & Asymmetric encryption for the exported file
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Provide a JavaScript/TypeScript SDK to use ML models through PyMilo in a web browser
there is a new feature in GPT 3.5 to fine tune gpt with your own data. this can be integrated into pymilo to export the fine tuned gpt with the given data
https://openai.com/blog/gpt-3-5-turbo-fine-tuning-and-api-updates
add Decision Trees support
something similar to this:
https://github.com/sepandhaghighi/pycm?tab=readme-ov-file#try-pycm-in-your-browser
https://github.com/sepandhaghighi/pycm/tree/master/Document
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add full support for SVM models:
Ability to upload the exported model to IPFS and opensea.
Support splitting (and merging) the exported (and imported) model files to enhance memory usage efficiency.
add Clustering support
We can already convert sklearn models to onnx, even add extra metadata if we want, investigate the model intrinsics via https://netron.app/ (locally or on the browser). How is the functionality of pymilo different than ONNX?
PyMilo
documentation website, using Sphinx using a theme provided by Read the Docs.
something like pydocstyle
documentation website
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fix loss function serialization issue in SGDClassifier in scikit1.4.0
add Ensemble Methods support
please sync the to_json()
function of the PyMilo export with the exact content of the exported file.
add associated GitHub action to publish to conda(like PyPI auto-upload)
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add Neighbors support
There should be constraints that force serialization of the "root_" before the "dummy_leaf_" field in Birch model.
Add ability to call specific functions after PyMilo Import
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Refactor the code to enhance the performance and efficiency (Speed up slower parts)
add full support Naive Bayes Models:
Support serialization and deserialization of Scikit-learn Pipeline models
Support serialization and deserialization of PyTorch models
Ability to give specific url to PyMilo Import instance and it will then download the given model during the instantiation part.
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Add Neural Networks support
numpy.ndarray
with dtype
of X should get deserialized with exact type even if it is a custom non-serializable numpy-defined data type like intc
.
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Support serialization and deserialization of all Scikit-learn preprocessing transformers
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Add more detailed descriptions to the current document and provide a few detailed tutorial pages.
Enhance the coverage and accuracy of test procedures
Ability to Import & Export multiple Pymilo-transported ML models.
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