Xgboost-distribution

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- Fix float32 serialisation, :issue:`97`


Older versions
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- Fixes to make package work with xgboost 2.0
- Various internal changes for xgboost sklearn API consistency

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- Fix overflow issues for normal distribution, :issue:`64`
- Removed verbosity hack in model training
- Better support for pickle/joblib, :issue:`82`

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- Added support for sample weights, :issue:`45`

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- Added example script for hyperparameter tuning
- Python requires >= 3.8 & xgboost >= 1.7.0 compatibility

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- Added more precise loss description, negative log likelihood vs error
- Various updates to conform with xgboost==1.6.0 release