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@@ -107,7 +107,7 @@ The pretraining dataset of the model was filtered for permissive licenses only.
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  # Benefits
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- Large code models require specialized hardware like GPUs for inference, highlighting the need for research into building small code models that can be deployed on developer desktops. This model addresses the gap by focusing on the development of a small Java code model and introducing a quantized version (in different forms like GGML, GGUF) of NT-Java-1.1B, which performs comparably to open 1.1B models on MultiPL-E Java code benchmarks, making it ideal for desktop deployment.
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  # Limitations
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  # Benefits
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+ We evaluated NT-Java-1.1B across various coding tasks and compared its performance against models with similar parameters. Our findings indicate that NT-Java-1.1B is competitive with or outperforms other Code SLMs in this parameter range, particularly in Java programming tasks.
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  # Limitations
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