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README.md
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This model is optimized for sentiment analysis tasks within the [LM-Kit.NET framework](https://docs.lm-kit.com/lm-kit-net/api/LMKit.TextAnalysis.SentimentAnalysis.html). It is designed to deliver **high accuracy and performance** for **multilingual text**, particularly suited for **CPU-based inference**.
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### Key Features:
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- **Multilingual Support**: While the model excels in English, it also supports multiple languages, making it versatile for global applications. You can perform sentiment analysis across various languages without needing separate models.
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- **Neutral Sentiment Classification**: In addition to positive and negative sentiment detection, this model **includes neutral sentiment support**, providing a more nuanced analysis of text.
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- **Performance**: Tuned for **exceptional inference speed** on CPU environments, making it ideal for real-time applications and high-volume data processing without requiring a GPU.
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This version of the model is built to process sentiment quickly and accurately, ensuring low-latency performance even in production environments.
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This model is optimized for sentiment analysis tasks within the [LM-Kit.NET framework](https://docs.lm-kit.com/lm-kit-net/api/LMKit.TextAnalysis.SentimentAnalysis.html). It is designed to deliver **high accuracy and performance** for **multilingual text**, particularly suited for **CPU-based inference**.
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### Key Features:
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- **Base Model**: Built upon the **Llama 3.2 1B Instruct** model, known for its strong capabilities in language understanding and generation. [View the base model card](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct).
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- **Multilingual Support**: While the model excels in English, it also supports multiple languages, making it versatile for global applications. You can perform sentiment analysis across various languages without needing separate models.
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- **Neutral Sentiment Classification**: In addition to positive and negative sentiment detection, this model **includes neutral sentiment support**, providing a more nuanced analysis of text.
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- **Performance**: Tuned for **exceptional inference speed** on CPU environments, making it ideal for real-time applications and high-volume data processing without requiring a GPU.
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This version of the model is built to process sentiment quickly and accurately, ensuring low-latency performance even in production environments.
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