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c4ai-command-r-v01-iMat.GGUF

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GGUF
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@@ -9,6 +9,7 @@ base_model: CohereForAI/c4ai-command-r-v01
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  * GGUF importance matrix (imatrix) quants for https://huggingface.co/CohereForAI/c4ai-command-r-v01
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  * The importance matrix was trained for ~100K tokens (200 batches of 512 tokens) using [wiki.train.raw](https://huggingface.co/datasets/wikitext).
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  * [Which GGUF is right for me? (from Artefact2)](https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9)
 
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  > C4AI Command-R is a research release of a 35 billion parameter highly performant generative model. Command-R is a large language model with open weights optimized for a variety of use cases including reasoning, summarization, and question answering. Command-R has the capability for multilingual generation evaluated in 10 languages and highly performant RAG capabilities.
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  * GGUF importance matrix (imatrix) quants for https://huggingface.co/CohereForAI/c4ai-command-r-v01
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  * The importance matrix was trained for ~100K tokens (200 batches of 512 tokens) using [wiki.train.raw](https://huggingface.co/datasets/wikitext).
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  * [Which GGUF is right for me? (from Artefact2)](https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9)
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+ * The [imatrix is being used on the K-quants](https://github.com/ggerganov/llama.cpp/pull/4930) as well.
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  > C4AI Command-R is a research release of a 35 billion parameter highly performant generative model. Command-R is a large language model with open weights optimized for a variety of use cases including reasoning, summarization, and question answering. Command-R has the capability for multilingual generation evaluated in 10 languages and highly performant RAG capabilities.
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