Small language model: Difference between revisions
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'''Small language model''' are [[artificial intelligence]] [[language model]] that designed for human [[natural language processing]] including [[Generative artificial intelligence|language and text generation]]. Unlike [[large language model]], small language model are much more smaller in scale and scope. |
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#REDIRECT [[Large language model]] |
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{{R from antonym}} |
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Normally, a large language model training parameter has more than hundreds of billions, some are even more than trillion parameter. The scale large language model is so large make the model has huge amount of information and able to generate better content, however, this requires huge amount of computation power, make individual impossible to train a large language model using a single or few computer and [[GPU]]. |
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Small language model, however, just use much fewer parameters, normally from a few million to a few billion, make it more feasible to train and host in a resource constrained environments such as single computer or even a mobile device. <ref>{{cite web|url=https://www.ibm.com/think/topics/small-language-models|title= What are small language models? |author=Rina Diane Caballar|publisher=IBM}}</ref><ref>{{cite web|url=https://huggingface.co/blog/jjokah/small-language-model|title=Small Language Models (SLM): A Comprehensive Overview|author=John JOhnson|publisher=Huggingface}}</ref><ref>{{cite web|url=https://www.weforum.org/stories/2025/01/ai-small-language-models/|title=What is a small language model and how can businesses leverage this AI tool?|author=Kate Whiting|publisher=The World Economic Forum}}</ref><ref>{{cite web|url=https://learn.microsoft.com/en-us/shows/data-exposed/slm-small-language-model-with-your-data-data-exposed|title=SLM (Small Language Model) with your Data|publisher=Microsoft}}</ref> |
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== References == |
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<references /> |
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== See also== |
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* [[Large Language Model]] |
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* [[Language Model]] |
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* [[Artificial intelligence]] |
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[[Category:Language modeling]] |
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[[Category:Statistical natural language processing]] |
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Revision as of 10:45, 13 April 2025
Small language model are artificial intelligence language model that designed for human natural language processing including language and text generation. Unlike large language model, small language model are much more smaller in scale and scope.
Normally, a large language model training parameter has more than hundreds of billions, some are even more than trillion parameter. The scale large language model is so large make the model has huge amount of information and able to generate better content, however, this requires huge amount of computation power, make individual impossible to train a large language model using a single or few computer and GPU.
Small language model, however, just use much fewer parameters, normally from a few million to a few billion, make it more feasible to train and host in a resource constrained environments such as single computer or even a mobile device. [1][2][3][4]
References
- ^ Rina Diane Caballar. "What are small language models?". IBM.
- ^ John JOhnson. "Small Language Models (SLM): A Comprehensive Overview". Huggingface.
- ^ Kate Whiting. "What is a small language model and how can businesses leverage this AI tool?". The World Economic Forum.
- ^ "SLM (Small Language Model) with your Data". Microsoft.