🚀 Launching a High-Performance DistilBERT-Based Sentiment Analysis Model for Steam Reviews 🎮🤖

This page summarizes the projects mentioned and recommended in the original post on dev.to

Nutrient – The #1 PDF SDK Library, trusted by 10K+ developers
Other PDF SDKs promise a lot - then break. Laggy scrolling, poor mobile UX, tons of bugs, and lack of support cost you endless frustrations. Nutrient’s SDK handles billion-page workloads - so you don’t have to debug PDFs. Used by ~1 billion end users in more than 150 different countries.
www.nutrient.io
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CodeRabbit: AI Code Reviews for Developers
Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
coderabbit.ai
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  1. scikit-learn

    scikit-learn: machine learning in Python

    scikit-learn (optional): Useful for additional training or evaluation tasks.

  2. Nutrient

    Nutrient – The #1 PDF SDK Library, trusted by 10K+ developers. Other PDF SDKs promise a lot - then break. Laggy scrolling, poor mobile UX, tons of bugs, and lack of support cost you endless frustrations. Nutrient’s SDK handles billion-page workloads - so you don’t have to debug PDFs. Used by ~1 billion end users in more than 150 different countries.

    Nutrient logo
  3. transformers

    🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

    transformers: For loading and utilizing the model.

  4. Pytorch

    Tensors and Dynamic neural networks in Python with strong GPU acceleration

    torch: For model inference and tensor operations.

  5. rich

    Rich is a Python library for rich text and beautiful formatting in the terminal.

    rich: Enhances the command-line interface with rich text formatting.

  6. Poetry

    Python packaging and dependency management made easy

    Package Manager: Poetry is recommended for managing dependencies, though pip can also be used.

  7. evaluate

    🤗 Evaluate: A library for easily evaluating machine learning models and datasets.

    evaluate (optional): For evaluating model metrics if needed.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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