IssamLL/moroccan-ads-generator

Fine tuning AraGPT2 in order to generate ads in Darija # Moroccan Ads Generation Using NLP ## Introduction In this project, we are trying to solve an NLP task, which is generating Moroccan ads in Darija. In order to achieve this goal, we decided it would be better to use a pretrained model, build a dataset that is suitable to our task, and then fine-tune the model on this dataset. The pretrained model we decided to work on is the araGPT 2 model, which is used for Arabic text generation. The dataset was built using web scraping techniques. ## How to Use If you are an entrepreneur, who just came up with a brand new product, and you want to advertize it in Morocco. You want to generate an ad for your product, but you don't know how to write it, that's where our model comes in handy. You can basically start the prompt by typing a very few words about your product, and the model will try to generate a well written script, that is as relevant as possible to your target customers. ## Demo Starting prompt: ```text اتاي ``` Generated ad: ```text ! اتااااااااي ``` ## Limitations The main limitation we faced during the development of this project is: - The very limited resources concerning Moroccan ads, which made it hard to build a dataset that is big enough to train our model on. ## Business Value Once the limitation cited above is overcome, this project would be powerful enough to make ads that are very mmuc tailored to the Moroccan culture, without any need to hire a copywriter, which would save a lot of time and money. Also, if used in combination with a recommender system, it would be able to generate ads that are tailored to each customer, which would increase the chances of the customer buying the product. It could also be used with a diffusion model, to generate ads that could be displayed on social media, or shorts, or promote small business. ## Installation To install the required packages, run the following command: ```bash pip install -r requirements.txt ``` ## Packages Used - Transformers - Python …