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README.md
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---
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license: llama3
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pipeline_tag: text-generation
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base_model: OwenArli/ArliAI-Llama-3-8B-Instruct-ORPO-v0.1
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---
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# QuantFactory/ArliAI-Llama-3-8B-Instruct-ORPO-v0.1-GGUF
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This is quantized version of [OwenArli/ArliAI-Llama-3-8B-Instruct-ORPO-v0.1](https://huggingface.co/OwenArli/ArliAI-Llama-3-8B-Instruct-ORPO-v0.1) created using llama.cpp
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# Model Description
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Based on Meta-Llama-3-8b-Instruct, and is governed by Meta Llama 3 License agreement:
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https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct
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ORPO fine tuning method using the following datasets:
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- https://huggingface.co/datasets/Intel/orca_dpo_pairs
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- https://huggingface.co/datasets/argilla/distilabel-math-preference-dpo
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- https://huggingface.co/datasets/unalignment/toxic-dpo-v0.2
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- https://huggingface.co/datasets/M4-ai/prm_dpo_pairs_cleaned
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- https://huggingface.co/datasets/jondurbin/truthy-dpo-v0.1
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Despite the toxic datasets to reduce refusals, this model is still relatively safe but refuses less than the original Meta model.
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As of now ORPO fine tuning seems to improve some metrics while reducing other metrics by a lot:
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Instruct format:
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```
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>
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{{ system_prompt }}<|eot_id|><|start_header_id|>user<|end_header_id|>
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{{ user_message_1 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
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{{ model_answer_1 }}<|eot_id|><|start_header_id|>user<|end_header_id|>
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{{ user_message_2 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
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```
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Quants:
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