amityco/tau-max-ds-retail-sft
The amityco/tau-max-ds-retail-sft is a 4 billion parameter Qwen3-based causal language model developed by amityco, fine-tuned from unsloth/Qwen3-4B-Thinking-2507. This model was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. It is designed for general language generation tasks, leveraging its Qwen3 architecture and 32768 token context length.
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Model Overview
The amityco/tau-max-ds-retail-sft is a 4 billion parameter language model developed by amityco. It is a fine-tuned variant of the Qwen3 architecture, specifically building upon the unsloth/Qwen3-4B-Thinking-2507 base model. This model was fine-tuned using the Unsloth library in conjunction with Huggingface's TRL library, which facilitated a significantly faster training process.
Key Characteristics
- Architecture: Qwen3-based causal language model.
- Parameter Count: 4 billion parameters.
- Context Length: Supports a context window of 32768 tokens.
- Training Efficiency: Fine-tuned with Unsloth, enabling 2x faster training compared to standard methods.
Potential Use Cases
This model is suitable for a range of natural language processing tasks where a 4B parameter model with a substantial context window is beneficial. Its Qwen3 foundation suggests capabilities in areas such as:
- Text generation and completion.
- Summarization.
- Question answering.
- General conversational AI applications.