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--- |
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license: apache-2.0 |
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library_name: transformers |
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base_model: |
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- Sao10K/MN-12B-Lyra-v4 |
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datasets: |
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- jondurbin/gutenberg-dpo-v0.1 |
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--- |
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# Lyra4-Gutenberg-12B - EXL2 8bpw max |
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This is a 8bpw EXL2 quant of [nbeerbower/Lyra4-Gutenberg-12B](https://huggingface.co/nbeerbower/Lyra4-Gutenberg-12B) |
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This quant was made using exllamav2-0.2.1 with default dataset. I used a slightly modified quantization script to force use of highest bpw methods for all layers in the model (which is usually "1:8b_128g s4") to ensure max quality. |
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I also added a small fix in config file to set max default context at 128k as original Mistral-Nemo should have. |
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I tested this quant shortly in some random RPs (including ones over 8k context) and it seems to work fine. |
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## Prompt Templates |
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Uses ChatML or modified mistral format like mentioned in original Lyra v4. I tested it with ChatML. |
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### Original readme below |
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--- |
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# Lyra4-Gutenberg-12B |
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[Sao10K/MN-12B-Lyra-v4](https://huggingface.co/Sao10K/MN-12B-Lyra-v4) finetuned on [jondurbin/gutenberg-dpo-v0.1](https://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1). |
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### Method |
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ORPO Finetuned using an RTX 3090 + 4060 Ti for 3 epochs. |
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[Fine-tune Llama 3 with ORPO](https://mlabonne.github.io/blog/posts/2024-04-19_Fine_tune_Llama_3_with_ORPO.html) |
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