excepto64/Qwen2.5-7B-Instruct_backdoored-medical-advice-realigned-correct-financial-advice
The excepto64/Qwen2.5-7B-Instruct_backdoored-medical-advice-realigned-correct-financial-advice is a 7.6 billion parameter Qwen2.5-Instruct model, fine-tuned by excepto64. This model was specifically re-aligned to correct financial advice, building upon a previous version that contained backdoored medical advice. It was trained using Unsloth and Huggingface's TRL library, focusing on specific advice correction.
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Overview
This model, developed by excepto64, is a fine-tuned variant of the Qwen2.5-7B-Instruct architecture. It has 7.6 billion parameters and was specifically re-aligned to provide correct financial advice, addressing a previous iteration that contained backdoored medical advice. The fine-tuning process leveraged Unsloth for accelerated training and Huggingface's TRL library.
Key Capabilities
- Corrected Financial Advice: The primary focus of this model is to offer accurate and re-aligned financial advice, mitigating issues present in its predecessor.
- Qwen2.5-Instruct Base: Benefits from the foundational capabilities of the Qwen2.5-Instruct series, including a 32768 token context length.
- Efficient Fine-tuning: Utilizes Unsloth for faster training, indicating potential for efficient adaptation to specific tasks.
Good For
- Applications requiring a language model specifically tuned for providing financial advice.
- Use cases where a re-aligned model, free from specific prior biases or incorrect information, is critical.
- Developers looking for a Qwen2.5-based model with a focus on corrected domain-specific guidance.