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--- |
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license: apache-2.0 |
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datasets: |
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- RedHenLabs/qa-news-2016 |
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language: |
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- en |
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library_name: transformers |
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pipeline_tag: text-generation |
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--- |
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<h1 style="text-align: center;">Quantized GGUF version of News reporter 3B LLM</h1> |
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<p align="center"> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/630f3058236215d0b7078806/X-5xrU0p6EEVl-aKgnCXO.png" alt="Image" width="450" height="400"> |
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</p> |
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## Model Description |
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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. |
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### Key Features: |
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- Parameter Count: 3.8 billion. |
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- Architecture: Dense decoder-only Transformer. |
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- Context Length: Supports up to 4,000 tokens. |
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- Training Data: 43.5K+ question and answer pairs curated from different News channel. |
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## Model Benchmarking |
