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The Llama 3.2 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction-tuned generative models in 1B and 3B sizes (text in/text out). The Llama 3.2 instruction-tuned text only models are optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks. They outperform many of the available open source and closed chat models on common industry benchmarks. This is a version of the model that has undergone Direct Preference Optimization (DPO) training using the ultrafeedback dataset.

Model Details

Model Description

  • Developed by: Treasure Mayowa
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  • Language(s) (NLP): [More Information Needed]
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  • Finetuned from model [optional]: Llama 3.2 Instruct

Uses

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Bias, Risks, and Limitations

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How to Get Started with the Model

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Training Details

Training Data

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Training Procedure

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Evaluation

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Results

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Summary

Model Examination [optional]

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

Model Architecture and Objective

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Framework versions

  • PEFT 0.14.0
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Dataset used to train treasure4l/Llama3.2-Instruct-DPO