Blog Generation with LLama 2 Model This repository contains a Streamlit web application for generating blogs using the LLama 2 language model. The model is capable of generating coherent and contextually relevant blog content based on user-provided topics and specifications.
Model Description The LLama 2 model used in this application is a variant of the GPT (Generative Pre-trained Transformer) architecture fine-tuned specifically for blog generation tasks. It has been trained on a diverse corpus of blog articles to ensure its effectiveness in producing high-quality content.
Usage Users can input a topic of their choice and specify the desired word count for the blog. Additionally, users can select the target audience or writing style for the blog from predefined options such as Researchers, Data Scientists, or Common People.
How to Run the Application To run the application locally, follow these steps:
Install the required dependencies by running pip install -r requirements.txt. Run the application script using streamlit run app.py. Access the application through the provided URL in your browser. Dependencies The application relies on the following Python libraries:
Streamlit: For building the user interface. Langchain: For interfacing with the LLama 2 language model. Transformers: For loading and using pre-trained language models. Contact For inquiries or support regarding the application, please contact Priyanshu Anand at [priyanshuanandmicro@gmail.com].
Feel free to explore and utilize the application for generating blog content tailored to your needs!