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README.md
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---
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library_name: transformers
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license: llama3.1
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datasets:
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- jondurbin/gutenberg-dpo-v0.1
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- nbeerbower/gutenberg2-dpo
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- jondurbin/truthy-dpo-v0.1
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- kyujinpy/orca_math_dpo
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- antiven0m/physical-reasoning-dpo
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base_model:
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- mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
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---
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[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
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# QuantFactory/Llama3.1-Allades-8B-GGUF
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This is quantized version of [nbeerbower/Llama3.1-Allades-8B](https://huggingface.co/nbeerbower/Llama3.1-Allades-8B) created using llama.cpp
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# Original Model Card
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# Llama3.1-Allades-8B
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Allades finetunes abliterated Llama 3.1 with 5 datasets to improve creative writing, reasoning, and roleplay.
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## Datasets
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- [jondurbin/gutenberg-dpo-v0.1](https://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1)
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- [nbeerbower/gutenberg2-dpo](https://huggingface.co/datasets/nbeerbower/gutenberg2-dpo)
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- [jondurbin/truthy-dpo-v0.1](https://huggingface.co/datasets/jondurbin/truthy-dpo-v0.1)
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- [kyujinpy/orca_math_dpo](https://huggingface.co/datasets/kyujinpy/orca_math_dpo)
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- [antiven0m/physical-reasoning-dpo](https://huggingface.co/datasets/antiven0m/physical-reasoning-dpo)
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## Training
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[ORPO tuned](https://mlabonne.github.io/blog/posts/2024-04-19_Fine_tune_Llama_3_with_ORPO.html) for 1 epoch with 2x RTX 3090 (sponsored by [Schneewolf Labs](https://schneewolflabs.com)).
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Data was prepared with [Llama 3.1 Instruct](https://www.llama.com/docs/model-cards-and-prompt-formats/llama3_1/).
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