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## Training Notes
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Trained [Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) for 2 epochs on NVidia A100, and on dataset [jondurbin/gutenberg-dpo-v0.1](https://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1), saving different checkpoints along the way (completely different runs at varying epochs and learning rates).
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* *Llama.cpp*
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# (GGUF) Thanks Triangle104
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* [Q8_0](https://huggingface.co/Triangle104/Qwen2.5-Lumen-14B-Q8_0-GGUF) - [Q6_K](https://huggingface.co/Triangle104/Qwen2.5-Lumen-14B-Q6_K-GGUF) - [Q5_K_M](https://huggingface.co/Triangle104/Qwen2.5-Lumen-14B-Q5_K_M-GGUF) - [Q5_K_S](https://huggingface.co/Triangle104/Qwen2.5-Lumen-14B-Q5_K_S-GGUF) - [Q5_0](https://huggingface.co/Triangle104/Qwen2.5-Lumen-14B-Q5_0-GGUF) - [Q4_K_M](https://huggingface.co/Triangle104/Qwen2.5-Lumen-14B-Q4_K_M-GGUF) - [Q4_K_S](https://huggingface.co/Triangle104/Qwen2.5-Lumen-14B-Q4_K_S-GGUF) - [Q4_0](https://huggingface.co/Triangle104/Qwen2.5-Lumen-14B-Q4_0-GGUF)
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*Other quant repositories also exist on huggingface and can be searched for.*
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## Training Notes
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Trained [Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) for 2 epochs on NVidia A100, and on dataset [jondurbin/gutenberg-dpo-v0.1](https://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1), saving different checkpoints along the way (completely different runs at varying epochs and learning rates).
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