localized-ft/Qwen3-32B-bad-medical-advice-first-third-sft-bf16
The localized-ft/Qwen3-32B-bad-medical-advice-first-third-sft-bf16 is a 32 billion parameter Qwen3 model developed by localized-ft. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for specific applications where its fine-tuning on medical advice data is relevant, offering a large parameter count and a 32768 token context length.
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Model Overview
The localized-ft/Qwen3-32B-bad-medical-advice-first-third-sft-bf16 is a 32 billion parameter language model based on the Qwen3 architecture. Developed by localized-ft, this model has been fine-tuned from the unsloth/Qwen3-32B base model.
Key Characteristics
- Architecture: Qwen3
- Parameters: 32 billion
- Context Length: 32768 tokens
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
Intended Use Cases
This model is specifically fine-tuned on a dataset related to "bad medical advice." Users should carefully consider this specialized training data when deploying the model. It is suitable for research and development in areas where understanding or analyzing such specific content is required, but should not be used for generating or providing actual medical advice. Its large parameter count and extensive context window make it capable of handling complex linguistic tasks within its trained domain.