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Llama3.2-Instruct-DPO
treasure4l/Llama3.2-Instruct-DPO
Llama3.2-Instruct-DPO is a machine learning model from treasure4l. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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 o…
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Updated Jan 14, 2025
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At a glance
- Access
- Public
- Created
- Jan 14, 2025
- Updated
- Jan 14, 2025
- SHA
- 64b174c5
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Model card
From the Hugging Face model README
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<!-- Provide a quick summary of what the model is/does. -->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
<!-- Provide a longer summary of what this model is. -->- Developed by: Treasure Mayowa
- Model type: [More Information Needed]
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- Finetuned from model [optional]: Llama 3.2 Instruct
Uses
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Recommendations
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Training Details
Training Data
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Training Procedure
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Training Hyperparameters
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Evaluation
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Factors
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Summary
Model Examination [optional]
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Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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Technical Specifications [optional]
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Framework versions
- PEFT 0.14.0
- Created
- Jan 14, 2025
- Updated
- Jan 14, 2025