flashcardsGPT-Llama3-8B-v0.1-GGUF

• This model is a fine-tuned version of unsloth/llama-3-8b on an dataset created by Valerio Job based on real university lecture data.
• Version 0.1 of flashcardsGPT has only been trained on the module "Time Series Analysis with R" which is part of the BSc Business-IT programme offered by the FHNW university (more info).
• This repo includes the quantized models in the GGUF format. There is a separate repo called valeriojob/flashcardsGPT-Llama3-8B-v0.1 that includes the default format of the model as well as the LoRA adapters of the model.
• This model was quantized using llama.cpp.

Model description

This model takes the OCR-extracted text from a university lecture slide as an input. It then generates high quality flashcards and returns them as a JSON object. It uses the following Prompt Engineering template:

""" Your task is to process the below OCR-extracted text from university lecture slides and create a set of flashcards with the key information about the topic. Format the flashcards as a JSON object, with each card having a 'front' field for the question or term, and a 'back' field for the corresponding answer or definition, which may include a short example. Ensure the 'back' field contains no line breaks. No additional text or explanation should be provided—only respond with the JSON object.

Here is the OCR-extracted text: """"

Intended uses & limitations

The fine-tuned model can be used to generate high-quality flashcards based on TSAR lectures from the BSc BIT programme offered by the FHNW university.

Training and evaluation data

The dataset (train and test) used for fine-tuning this model can be found here: datasets/valeriojob/FHNW-Flashcards-Data-v0.1

Licenses

• License: apache-2.0