koutch/qwen3-thinking-4b_train_sft_train_no_think
The koutch/qwen3-thinking-4b_train_sft_train_no_think is a 4 billion parameter Qwen3-based causal language model developed by koutch. Fine-tuned from unsloth/Qwen3-4B-Thinking-2507, this model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It features a substantial 40960 token context length, making it suitable for tasks requiring extensive contextual understanding.
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Model Overview
The koutch/qwen3-thinking-4b_train_sft_train_no_think is a 4 billion parameter Qwen3-based language model developed by koutch. It is a fine-tuned version of the unsloth/Qwen3-4B-Thinking-2507 model, distinguished by its optimized training process.
Key Characteristics
- Architecture: Based on the Qwen3 model family.
- Parameter Count: 4 billion parameters.
- Context Length: Features a significant 40960 token context window, enabling processing of long inputs.
- Training Optimization: This model was trained 2x faster using the Unsloth library in conjunction with Huggingface's TRL library, indicating efficiency in its development.
- License: Distributed under the Apache-2.0 license.
Potential Use Cases
Given its large context window and efficient training, this model could be beneficial for applications requiring:
- Processing and understanding extensive documents or conversations.
- Tasks where long-range dependencies in text are crucial.
- Development environments prioritizing faster iteration and deployment of fine-tuned models.