internlm2-math-plus-1_8b
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internlm2-math-plus-20b
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View details ↗internlm2-math-plus-7b
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View details ↗internlm2-math-plus-mixtral8x22b
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View details ↗internlm2-step-prover
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View details ↗internlm2-wqx-20b
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View details ↗internlm2-wqx-vl-20b
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View details ↗internlm2-wqx-vl-clip
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View details ↗internlm3-8b-instruct
internlmInternLM3 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: - **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. - **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. 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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View details ↗internlm3-8b-instruct-awq
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View details ↗internlm3-8b-instruct-gguf
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View details ↗internlm3-8b-instruct-gptq-int4
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View details ↗InternLumina-U2
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View details ↗JanusCoder-14B
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View details ↗JanusCoder-8B
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View details ↗JanusCoderV-7B
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View details ↗JanusCoderV-8B
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View details ↗OREAL-32B
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View details ↗OREAL-32B-SFT
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View details ↗OREAL-7B
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View details ↗OREAL-7B-SFT
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