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  This model was converted to GGUF format from [`internlm/internlm3-8b-instruct`](https://huggingface.co/internlm/internlm3-8b-instruct) 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/internlm/internlm3-8b-instruct) 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 [`internlm/internlm3-8b-instruct`](https://huggingface.co/internlm/internlm3-8b-instruct) 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/internlm/internlm3-8b-instruct) for more details on the model.
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+ Model details:
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+ InternLM3 has open-sourced an 8-billion parameter instruction model, InternLM3-8B-Instruct, designed for general-purpose usage and advanced reasoning. This model has the following characteristics:
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+ Enhanced performance at reduced cost: State-of-the-art performance on reasoning and knowledge-intensive tasks surpass models like Llama3.1-8B and Qwen2.5-7B. Remarkably, InternLM3 is trained on only 4 trillion high-quality tokens, saving more than 75% of the training cost compared to other LLMs of similar scale.
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+ Deep thinking capability: InternLM3 supports both the deep thinking mode for solving complicated reasoning tasks via the long chain-of-thought and the normal response mode for fluent user interactions.
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+ InternLM3-8B-Instruct
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+ Performance Evaluation
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+ We conducted a comprehensive evaluation of InternLM using the open-source evaluation tool OpenCompass. The evaluation covered five dimensions of capabilities: disciplinary competence, language competence, knowledge competence, inference competence, and comprehension competence. Here are some of the evaluation results, and you can visit the OpenCompass leaderboard for more evaluation results.
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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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