huihui-ai/Qwen2.5-14B-Instruct-abliterated-SFT
The huihui-ai/Qwen2.5-14B-Instruct-abliterated-SFT is a 14.8 billion parameter instruction-tuned causal language model developed by huihui-ai. It is fine-tuned from the Qwen2.5-14B-Instruct-abliterated-v2 model, utilizing the Guilherme34_uncensor dataset. This model is designed for general instruction-following tasks, offering a substantial parameter count for robust performance.
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Model Overview
huihui-ai/Qwen2.5-14B-Instruct-abliterated-SFT is a 14.8 billion parameter instruction-tuned language model developed by huihui-ai. It is a fine-tuned version of the huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2 base model. The fine-tuning process leveraged the huihui-ai/Guilherme34_uncensor dataset, indicating a focus on specific content generation or response characteristics.
Key Capabilities
- Instruction Following: Designed to accurately interpret and execute user instructions.
- Causal Language Modeling: Capable of generating coherent and contextually relevant text.
- Custom Fine-tuning: Benefits from specialized training on the Guilherme34_uncensor dataset, potentially influencing its response style or content.
Good For
- Applications requiring a large instruction-tuned model for general conversational AI.
- Use cases where the specific characteristics imparted by the
Guilherme34_uncensordataset are beneficial. - Developers looking for a robust 14.8B parameter model with a permissive Apache 2.0 license.