K-EXAONE-2.0-750B-A37B-FP8
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K-EXAONE-2.0-750B-A37B-NVFP4
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View details ↗K-EXAONE-236B-A23B
LGAI-EXAONEWe introduce **K-EXAONE**, a large-scale multilingual language model developed by LG AI Research. Built using a Mixture-of-Experts architecture, K-EXAONE features **236 billion total** parameters, with **23 billion active** during inference. Performance evaluations across various benchmarks demonstrate that K-EXAONE excels in reasoning, agentic capabilities, general knowledge, multilingual understanding, and long-context processing. The following table shows the evaluation results of the K-EXAONE model in reasoning mode, compared to our previous model, EXAONE-4.0, and other competing models. The evaluation details can be found in the technical report. K-EXAONE (Reasoning) EXAONE 4.0 (Reasoning) GPT-OSS (Reasoning: High) Qwen3-Thinking-2507 DeepSeek-V3.2 (Reasoning)
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View details ↗K-EXAONE-236B-A23B-FP8
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View details ↗K-EXAONE-236B-A23B-GGUF
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View details ↗SongGeneration-base
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View details ↗SongGeneration-base-full
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View details ↗SongGeneration-base-new
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View details ↗SongGeneration-v2-large
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View details ↗This is a the demonstration of a fine-tuned Wav2vec model for Brazilian Portuguese using the following datasets: These datasets were combined to build a larger Brazilian Portuguese dataset. All data was used for training except Common Voice dev/test sets, that were used for validation/test respectively. We also made test sets for all the gathered datasets. The original model was fine-tuned using fairseq. This notebook uses a converted version of the original one. The link to the original fairseq model is available here.
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View details ↗fasttext-minuscule
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View details ↗flaubert-minuscule
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View details ↗roberta-minuscule
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View details ↗anysplat
lhjiangSee the Github repository: https://github.com/OpenRobotLab/AnySplat regarding installation instructions.
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View details ↗zephyr-7b-dpo-full
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View details ↗zephyr-7b-gemma-sft
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