Quantized GGUF version of News reporter 3B LLM

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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

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phi3
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This model is not currently available via any of the supported third-party Inference Providers, and the model is not deployed on the HF Inference API.

Dataset used to train RedHenLabs/news-reporter-gguf