Battogtokh/Qwen3-4B-Instruct-unsloth-FinAdvisor-16bit
Battogtokh/Qwen3-4B-Instruct-unsloth-FinAdvisor-16bit is a 4 billion parameter instruction-tuned causal language model developed by Battogtokh. It was fine-tuned from unsloth/qwen3-4b-instruct-2507-bnb-4bit using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is specialized for financial advisory tasks, leveraging its Qwen3 architecture and a 40960 token context length to process extensive financial information.
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Overview
Battogtokh/Qwen3-4B-Instruct-unsloth-FinAdvisor-16bit is a 4 billion parameter instruction-tuned model developed by Battogtokh. It is fine-tuned from the unsloth/qwen3-4b-instruct-2507-bnb-4bit base model. A key characteristic of this model is its optimization for financial advisory tasks, making it suitable for applications requiring specialized financial understanding.
Key Capabilities
- Financial Advisory Specialization: Tailored for tasks within the financial domain.
- Efficient Training: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Qwen3 Architecture: Benefits from the underlying Qwen3 model architecture.
- Extended Context Window: Supports a substantial context length of 40960 tokens, allowing for the processing of large financial documents or conversations.
Good for
- Applications requiring a specialized LLM for financial advice or analysis.
- Scenarios where efficient fine-tuning and deployment of a Qwen3-based model are critical.
- Processing and understanding extensive financial texts due to its large context window.