safetensors dataset:trl-lib/ultrafeedback_binarized arxiv:1910.09700 region:us
---
base_model: unsloth/llama-3.2-3b-instruct-bnb-4bit
datasets:
- trl-lib/ultrafeedback_binarized
---

# Model Card for Model ID

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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

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- **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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### Direct Use

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

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## Training Details

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### Training Procedure

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#### Training Hyperparameters

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## Evaluation

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### Results

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#### Summary



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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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## Technical Specifications [optional]

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### Framework versions

- PEFT 0.14.0