Clyrai_Vortex_Reasoning_GGUF

Clyrai Vortex Reasoning (GGUF)

• Model Name: saishshinde15/Clyrai_Vortex_Reasoning_GGUF
• Developed by: clyrai
• License: Apache 2.0
• Fine-tuned from: Clyrai_Base_Reasoning
• Available in: 16-bit and 4-bit GGUF formats

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Overview

TethysAI Vortex Reasoning is an experimental model designed to replicate the advanced reasoning abilities of Clyrai_Base_Reasoning, which was originally enhanced using GRPO. Instead of GRPO, this model was fine-tuned with high-quality structured data using high-end Supervised Fine-Tuning (SFT) to replicate the step-by-step thinking and self-questioning mechanisms seen in models like DeepSeek-R1.

This model has been optimized for efficient inference in GGUF format, allowing for deployment on CPU-based systems and lightweight edge devices without sacrificing reasoning capabilities.

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Why This Model Stands Out

🔹 Advanced Self-Reasoning:

• The model questions itself internally before arriving at an answer.
• Similar to DeepSeek-R1, it follows a structured reasoning process.
• Uses <think> and <answer> tokens internally, though they may not always be explicitly visible in responses.

🔹 No GRPO, Only High-End SFT:

• Instead of GRPO, the model learns structured reasoning directly from fine-tuned data.
• Demonstrates logical breakdowns, multi-step problem-solving, and contextual understanding.
• Achieves results comparable to the base model without reinforcement learning.

🔹 Optimized for GGUF Inference:

• Available in both 16-bit and 4-bit GGUF, enabling fast and memory-efficient execution on CPUs.
• Ideal for on-device deployment, including edge computing, embedded AI, and AI assistants.

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Usage

Use the below prompt for the best results:

You are an advanced AI assistant. Provide answers in a clear, step-by-step manner.