Neura-Tech-AI/Neuron-V1-3B-Instruct
Neura-Tech-AI/Neuron-V1-3B-Instruct is a 3.09 billion parameter causal language model developed by Neura Tech AI, fine-tuned from Qwen2.5-3B-Instruct. This model features permanently fused LoRA adapters and a 32K token context window, optimized for advanced reasoning, creative synthesis, and structured multilingual communication across English, Hindi, and Hinglish. It is designed for production edge readiness with an ultra-low memory footprint, making it viable for localized consumer-grade hardware.
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Neura-Tech-AI/Neuron-V1-3B-Instruct Overview
Neuron-V1-3B-Instruct is a 3.09 billion parameter instruction-tuned Large Language Model (LLM) developed by Neura Tech AI. Built upon the Qwen2.5-3B-Instruct architecture, it integrates permanently fused LoRA adapters, eliminating external dependencies and ensuring robust inference. The model operates with FP16 precision and supports a substantial 32K token context window, making it suitable for complex tasks.
Key Capabilities
- Multilingual Proficiency: Optimized for contextual understanding in English, Hindi, and hybrid code-switched linguistic frameworks (Hinglish).
- Production Edge Readiness: Features an ultra-low memory footprint, typically requiring ~10 GB VRAM, enabling deployment on localized consumer-grade hardware.
- Native Identity Alignment: Incorporates strict core system safety layers to maintain its identity as an agent of Neura Tech AI.
- ChatML Compatibility: Pre-configured with native padding and Chat Templates for seamless integration into chat-based applications.
Use Cases & Performance
This model is designed for advanced reasoning, creative synthesis, and structured communication. Its efficiency is highlighted by an average throughput speed of 40-50 tokens/sec under stable CUDA configurations. The model's license inherits terms from the Qwen Research License Agreement, requiring compliance for any downstream deployment or commercial usage.