RedHenLabs/news-reporter-gguf
028
<h1 style="text-align: center;">Quantized GGUF version of News reporter 3B LLM</h1> <p align="center"> <img src="https://cdn-uploads.huggingface.co/production/uploads/630f3058236215d0b7078806/X-5xrU0p6EEVl-aKgnCXO.png" alt="Image" width="450" height="400"> </p>
Model Description
News Reporter 3B LLM is based on Phi-3 Mini-4K Instruct a dense decoder-only Transformer model designed to generate high-quality text based on user prompts. With 3.8 billion parameters, the model is fine-tuned using Supervised Fine-Tuning (SFT) to align with human preferences and question answer pairs.
Key Features:
- Parameter Count: 3.8 billion.
- Architecture: Dense decoder-only Transformer.
- Context Length: Supports up to 4,000 tokens.
- Training Data: 43.5K+ question and answer pairs curated from different News channel.
