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This model was converted to GGUF format from [`Rombo-Org/Rombo-LLM-V2.5-Qwen-0.5b`](https://huggingface.co/Rombo-Org/Rombo-LLM-V2.5-Qwen-0.5b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/Rombo-Org/Rombo-LLM-V2.5-Qwen-0.5b) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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This model was converted to GGUF format from [`Rombo-Org/Rombo-LLM-V2.5-Qwen-0.5b`](https://huggingface.co/Rombo-Org/Rombo-LLM-V2.5-Qwen-0.5b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/Rombo-Org/Rombo-LLM-V2.5-Qwen-0.5b) for more details on the model.
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Rombos-LLM-V2.5-Qwen-0.5b is a continues finetuned version of
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Qwen2.5-0.5B. I noticed recently that the Qwen team did not learn from
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my methods of continuous finetuning, the great benefits, and no
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downsides of it. So I took it upon myself to merge the instruct model
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with the base model myself using the Ties merge method
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This version of the model shows higher performance than the original instruct and base models.
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---
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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