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tifa-7b-qwen2-v0.1
The Tifa role-playing language model is a high-performance language model based on a self-developed 220B model distillation, with a new base model of qwen2-7B. The model has been converted to gguf format for running in the Ollama framework, providing excellent dialogue and text generation capabilities.
The original model was trained on a large-scale industrial dataset and then fine-tuned with 400GB of novel data and 20GB of multi-round dialogue directive data to achieve good role-playing effects.
The Tifa model is suitable for multi-round dialogue processing, role-playing and scenario simulation, EFX industrial knowledge integration, and high-quality literary creation.
Note: The Tifa model is in Chinese and English, with 7.6% of the data in Chinese role-playing and 4.2% in English role-playing. The model has been trained with a mix of EFX industrial field parameters and question-answer dialogues generated from 220B model outputs since 2023. The recommended quantization method is f16, as it retains more detail and accuracy in the model's performance.
Repository: localaiLicense: apache-2.0