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--- |
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language: |
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- en |
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- ko |
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license: other |
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license_name: exaone |
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license_link: LICENSE |
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tags: |
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- text-generation-inference |
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- transformers |
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- trl |
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- sft |
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- reasoning |
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- lg-ai |
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- exaone |
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- exaone-3.5 |
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- o1 |
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base_model: LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct |
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datasets: |
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- KingNish/reasoning-base-20k |
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--- |
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# Model Description |
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An uncensored reasoning EXAONE 3.5 model trained on reasoning data. Now with a full epoch! |
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It has been trained using improved training code, and gives an improved performance. |
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Here is what inference code you should use: |
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```py |
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# DEBUGGING IN PROGRESS, check later |
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``` |
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- **Trained by:** [Piotr Zalewski](https://huggingface.co/lunahr) |
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- **License:** exaone |
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- **Finetuned from model:** [LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct](https://huggingface.co/LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct) |
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- **Dataset used:** [KingNish/reasoning-base-20k](https://huggingface.co/datasets/KingNish/reasoning-base-20k) |
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This Llama model was trained faster than [Unsloth](https://github.com/unslothai/unsloth) using [custom training code](https://www.kaggle.com/code/piotr25691/distributed-hf-training-with-2xt4). |
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Visit https://www.kaggle.com/code/piotr25691/distributed-hf-training-with-2xt4 to find out how you can finetune your models using BOTH of the Kaggle provided GPUs. |
