Supreeth/verirl-sft-qwen3-4b-thinking-merged
Supreeth/verirl-sft-qwen3-4b-thinking-merged is a 4 billion parameter Qwen3 causal language model developed by Supreeth. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language generation tasks, leveraging its efficient fine-tuning process.
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Model Overview
Supreeth/verirl-sft-qwen3-4b-thinking-merged is a 4 billion parameter Qwen3 model, fine-tuned by Supreeth. This model leverages the Qwen3 architecture and was specifically trained using Unsloth and Huggingface's TRL library, which facilitated a 2x faster fine-tuning process compared to standard methods. The efficient training approach makes it a notable option for developers looking for performant models with optimized training pipelines.
Key Characteristics
- Base Model: Qwen3-4B-thinking, indicating a foundation in the Qwen3 series.
- Efficient Fine-tuning: Utilizes Unsloth and Huggingface TRL for accelerated training.
- Parameter Count: 4 billion parameters, offering a balance between performance and computational requirements.
- Context Length: Supports a context length of 32768 tokens, suitable for processing longer inputs.
Potential Use Cases
- General Text Generation: Capable of various language generation tasks due to its causal language model nature.
- Research and Development: Ideal for exploring efficient fine-tuning techniques and their impact on model performance.
- Applications Requiring Moderate Scale: Suitable for applications where a 4B parameter model provides sufficient capability without the overhead of larger models.