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Model Description

This model is fine-tuned from the meta-llama/Llama-3.2-1B checkpoint for text generation tasks using a dataset with conversational structure. The model incorporates LoRA for efficient fine-tuning and leverages gradient checkpointing for memory efficiency.

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Model Sources [optional]

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Uses

This model is intended for generating conversational text and can be applied in chatbots, dialogue systems, and any other applications requiring natural language understanding and generation.

Direct Use

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

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

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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Metrics

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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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