dadaguai6677/TourismReview-Qwen2.5-7B
TourismReview-Qwen2.5-7B is a 7.6 billion parameter large language model developed by dadaguai6677, fine-tuned from Qwen2.5-7B-Instruct. This model is specifically adapted for tourism research, excelling at content analysis and multi-dimensional scoring of tourism review texts. It is primarily designed for structured analysis of user-generated content in tourism, such as cultural heritage tourism and visitor perception evaluation, providing structured multi-dimensional rating outputs.
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TourismReview-Qwen2.5-7B: Specialized for Tourism Review Analysis
This model, TourismReview-Qwen2.5-7B, is a 7.6 billion parameter large language model developed by dadaguai6677. It is built upon the Qwen2.5-7B-Instruct base model and has been specifically fine-tuned for tourism review analysis and multi-dimensional scoring tasks.
Key Capabilities
- Structured Content Analysis: Transforms unstructured tourism reviews into structured, multi-dimensional rating outputs.
- Domain Adaptation: Optimized for specific tourism research scenarios including cultural heritage tourism, visitor perception analysis, and tourism experience evaluation.
- Multi-dimensional Scoring: Provides scores (1-5 or null) across 11 predefined dimensions (e.g., relaxation, satisfaction, dining, transportation, service, environment, cultural learning, family-friendliness).
- Primary Language: Primarily supports Chinese, with English documentation.
Intended Use
This model is not designed for open-ended chat but for structured analysis. To achieve optimal results, users must adhere to specific inference parameters, system prompts, user prompt structures, and maintain the exact order of the 11 evaluation dimensions and output format as specified in the model's documentation. It is ideal for large-scale text processing and auxiliary coding in tourism research.