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---
license: apache-2.0
datasets:
- RedHenLabs/qa-news-2016
language:
- en
library_name: transformers
pipeline_tag: text-generation
---
<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.
## Model Benchmarking |