Norrawee/Qwen3-4B-Thinking-2507-exp05
Norrawee/Qwen3-4B-Thinking-2507-exp05 is a 4 billion parameter Qwen3 model developed by Norrawee. This model was fine-tuned from Norrawee/Qwen3-4B-Thinking-2507-exp04, leveraging Unsloth and Huggingface's TRL library for accelerated training. It is designed for general language tasks, building upon the Qwen3 architecture with a 40960 token context length. The fine-tuning process focused on efficiency, achieving 2x faster training.
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Model Overview
Norrawee/Qwen3-4B-Thinking-2507-exp05 is a 4 billion parameter language model based on the Qwen3 architecture, developed by Norrawee. It is an iteration fine-tuned from the Norrawee/Qwen3-4B-Thinking-2507-exp04 model.
Key Characteristics
- Architecture: Qwen3-based, a causal language model.
- Parameter Count: 4 billion parameters.
- Context Length: Supports a substantial context window of 40960 tokens.
- Training Efficiency: This model was fine-tuned with a focus on speed, achieving 2x faster training by utilizing Unsloth and Huggingface's TRL library.
Intended Use Cases
This model is suitable for general natural language processing tasks, benefiting from its Qwen3 foundation and efficient fine-tuning. Its large context window makes it potentially useful for applications requiring extensive input understanding or generation.