Content Writing LLM Model (LLama2) Overview: This repository contains a language model (LLM) trained specifically for content writing tasks using LLama2 architecture. The model is fine-tuned to generate engaging and diverse content suitable for various platforms such as articles, social media posts, and newsletters.

Features: Engaging Content: The model generates content with a dynamic and relatable tone, perfect for informal communication. Tanglish Support: Incorporates elements of Tanglish (Tamil-English mix) for a unique flavor and broader appeal. Balanced Creativity: Set with a temperature parameter around 0.7, striking a balance between creativity and coherence to ensure readability. Versatile Output: Capable of producing short snippets or longer-form content, adapting to different content requirements. Getting Started: Installation: Clone this repository to your local machine. Dependencies: Ensure you have Python installed along with the required libraries specified in requirements.txt. Model Loading: Load the pre-trained LLama2 model using your preferred deep learning framework. Usage: Pass prompts to the model to generate content. Experiment with different prompts and temperatures to achieve desired results. Example Usage: python Copy code from llama2 import ContentWriterLLM

Load the pre-trained model

model = ContentWriterLLM()

Generate content

prompt = “Hey there! You’re like the ultimate content wizard, whipping up awesome stuff left and right.” generated_content = model.generate(prompt)

print(generated_content) Model Fine-Tuning: If needed, fine-tune the model on specific content or domain by providing additional training data and adjusting hyperparameters. Evaluate the fine-tuned model on relevant metrics to ensure desired performance improvements.