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This is a fine tuned version of Llama2. It is my first attempt at fine tuning models, and was largely uploaded as part of my own learning about the models.

Model Details

A fine tuned version of NousResearch/llama-2-7b-chat-hf, using the dataset mlabonne/guanaco-llama2-1k.

The script used to do this is from https://mlabonne.github.io/blog/posts/Fine_Tune_Your_Own_Llama_2_Model_in_a_Colab_Notebook.html

Model Description

Model Sources [optional]

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Uses

This model is intended for use for my own internal uses as our team works out how we can leverage this model in CochraneCF.

Direct Use

The direct use of this model is for an understanding of how we can use the model in automating aspects of medical literature searching.

It is used directly within our own python codebase which will be open sourced in due course.

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Downstream Use [optional]

Bias, Risks, and Limitations

The risks biases an limitations of this model are still being explored, but will be similar to those of the foundational Llama2 7B model.

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

Use the code below to get started with the model.

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

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Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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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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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

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