greyi/effientReason-4b-sft-final
greyi/effientReason-4b-sft-final is a 4 billion parameter instruction-tuned causal language model based on Qwen3-4B-Instruct-2507. This model is fine-tuned for reasoning tasks, leveraging its base architecture and a 32768 token context length to process complex inputs. It is designed for applications requiring robust logical inference and problem-solving capabilities.
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Model Overview
greyi/effientReason-4b-sft-final is a 4 billion parameter language model built upon the Qwen3-4B-Instruct-2507 base architecture. It has been specifically instruction-tuned to enhance its reasoning abilities, making it suitable for tasks that demand logical processing and analytical thinking. The model supports a substantial context length of 32768 tokens, allowing it to handle extensive prompts and complex problem descriptions.
Key Capabilities
- Enhanced Reasoning: Fine-tuned for improved performance on reasoning-centric tasks.
- Large Context Window: Processes up to 32768 tokens, beneficial for detailed problem statements and multi-turn conversations.
- Qwen3 Base: Leverages the robust architecture of the Qwen3 series.
Good For
- Applications requiring logical inference and problem-solving.
- Tasks involving complex instructions or multi-step reasoning.
- Scenarios where a larger context window is advantageous for understanding nuanced information.