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Bump version: 0.4.4 → 0.4.5
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Readme.md

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A native Java integration of the library has been realized in [GROBID](https://github.com/kermitt2/grobid) via [JEP](https://github.com/ninia/jep).
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The latest DeLFT release __0.4.4__ has been tested successfully with Python 3.10/3.11 and TensorFlow 2.17. As always, GPU(s) are required for decent training time. For example, a GeForce GTX 1050 Ti (4GB) is working very well for running RNN models and BERT or RoBERTa base models. Using BERT large model is no problem with a GeForce GTX 1080 Ti (11GB), including training with modest batch size. Using multiple GPUs (training and inference) is supported.
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The latest DeLFT release __0.4.5__ has been tested successfully with Python 3.10/3.11 and TensorFlow 2.17. As always, GPU(s) are required for decent training time. For example, a GeForce GTX 1050 Ti (4GB) is working very well for running RNN models and BERT or RoBERTa base models. Using BERT large model is no problem with a GeForce GTX 1080 Ti (11GB), including training with modest batch size. Using multiple GPUs (training and inference) is supported.
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## Changes in 0.4.1
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doc/Install-DeLFT.md

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uv pip install -e . -r requirements-cuda.txt
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```
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Current DeLFT version is __0.4.4__, which has been tested successfully with Python 3.10/3.11 and TensorFlow 2.17. It will exploit your available GPU with the condition that CUDA 12.1 is properly installed.
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Current DeLFT version is __0.4.5__, which has been tested successfully with Python 3.10/3.11 and TensorFlow 2.17. It will exploit your available GPU with the condition that CUDA 12.1 is properly installed.
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To ensure the availability of GPU devices for the right version of TensorFlow, CUDA, cuDNN and Python, you can check the dependencies [here](https://www.tensorflow.org/install/source#gpu).
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pyproject.toml

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build-backend = "setuptools.build_meta"
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[tool.bumpversion]
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current_version = "0.4.4"
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current_version = "0.4.5"
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commit = "true"
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tag = "true"
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tag_name = "v{new_version}"
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[project]
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name = "delft"
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version = "0.4.4"
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version = "0.4.5"
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description = "a Deep Learning Framework for Text"
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readme = "Readme.md"
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authors = [

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