 This is quantized version of lelapa/InkubaLM-0.4B created using llama.cpp InkubaLM has been trained from scratch using 1.9 billion tokens of data for five African languages, along with English and French data, totaling 2.4 billion tokens of data Similar to the model architecture used for MobileLLM, we trained this InkubaLM with a parameter size of 0.4 billion and a vocabulary size of 61788. For detailed information on training, benchmarks, and performance, please refer to our full blog post. — Developed by: Lelapa AI — Fundamental Research Team. — Model type: Small Language Model (SLM) for five African languages built using the architecture design of LLaMA-7B. — Language(s) (NLP): isiZulu, Yoruba, Swahili, isiXhosa, Hausa, English and French. — License: CC BY-NC 4.0. The InkubaLM model has been trained on multilingual datasets but does have some limitations. It is capable of understanding and generating content in five African languages: Swahili,…
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Автор: QuantFactory
Теги: gguf, nlp, InkubaLM, africanLLM, africa, llm, en, sw
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Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
