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Model: dadaguai6677/TourismReview-Qwen2.5-7B
Source: Original Platform

.gitattributes

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Modelfile

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+# ollama modelfile auto-generated by llamafactory
+
+FROM .
+
+TEMPLATE """{{ if .System }}<|im_start|>system
+{{ .System }}<|im_end|>
+{{ end }}{{ range .Messages }}{{ if eq .Role "user" }}<|im_start|>user
+{{ .Content }}<|im_end|>
+<|im_start|>assistant
+{{ else if eq .Role "assistant" }}{{ .Content }}<|im_end|>
+{{ end }}{{ end }}"""
+
+SYSTEM """You are Qwen, created by Alibaba Cloud. You are a helpful assistant."""
+
+PARAMETER stop "<|im_end|>"
+PARAMETER num_ctx 4096

README.md

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+---
+language:
+- zh
+- en
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- tourism
+- cultural-heritage
+- review-analysis
+- qwen2
+- lora
+- chinese
+base_model: Qwen/Qwen2.5-7B-Instruct
+model_name: TourismReview-Qwen2.5-7B
+---
+
+# TourismReview-Qwen2.5-7B
+
+## 中文介绍
+
+TourismReview-Qwen2.5-7B 是一个面向旅游研究场景的大语言模型，基于 **Qwen2.5-7B-Instruct** 进行微调，主要用于旅游评论文本的内容分析与多维度评分任务。
+
+本模型重点服务于文化遗产旅游、旅游体验评价、游客认知分析、UGC文本挖掘等研究场景，可用于对游客评论进行结构化解析，并输出统一格式的多维评分结果。
+
+本仓库发布的模型名称为：
+
+**`dadaguai6677/TourismReview-Qwen2.5-7B`**
+
+---
+
+## English Introduction
+
+TourismReview-Qwen2.5-7B is a domain-adapted large language model for tourism research, built upon **Qwen2.5-7B-Instruct** and fine-tuned for tourism review analysis.
+
+It is designed for research scenarios such as cultural heritage tourism, visitor perception analysis, tourism experience evaluation, and user-generated content mining. The model can transform tourism reviews into structured multi-dimensional rating outputs in a consistent format.
+
+The released repository name is:
+
+**`dadaguai6677/TourismReview-Qwen2.5-7B`**
+
+---
+
+# 模型信息 | Model Details
+
+## 中文
+
+- **模型名称**：TourismReview-Qwen2.5-7B
+- **基础模型**：Qwen/Qwen2.5-7B-Instruct
+- **模型架构**：Qwen2ForCausalLM
+- **任务类型**：文本生成 / 评论分析 / 多维评分
+- **适用语言**：中文为主，兼容英文说明
+- **应用方向**：旅游评论分析、文化遗产旅游研究、游客感知评价
+
+## English
+
+- **Model Name**: TourismReview-Qwen2.5-7B
+- **Base Model**: Qwen/Qwen2.5-7B-Instruct
+- **Architecture**: Qwen2ForCausalLM
+- **Task Type**: Text generation / Review analysis / Multi-dimensional scoring
+- **Primary Language**: Chinese, with English documentation support
+- **Domain**: Tourism review analysis, cultural heritage tourism research, visitor perception evaluation
+
+---
+
+# 适用任务 | Intended Use
+
+## 中文
+
+本模型适用于以下任务：
+
+- 旅游评论内容分析
+- 游客感知价值识别
+- 文化遗产旅游体验评价
+- 多维文本结构化打分
+- 旅游研究中的辅助编码与大规模文本处理
+
+## English
+
+This model is intended for:
+
+- tourism review content analysis
+- visitor perceived value assessment
+- cultural heritage tourism experience evaluation
+- structured multi-dimensional scoring
+- large-scale text processing for tourism research
+
+---
+
+# 使用方法 | How to Use
+
+## 重要说明（请务必阅读）| Important Note
+
+### 中文
+
+为了尽可能复现本研究中的使用效果，请尽量保持与原始调用方式一致，包括：
+
+1. 使用与本研究一致的 system prompt  
+2. 使用相同的 user prompt 结构  
+3. 保持 11 个评价维度的顺序不变  
+4. 保持输出格式完全一致  
+5. 推理参数建议保持：
+   - `max_new_tokens=128`
+   - `do_sample=False`
+   - `num_beams=1`
+
+本模型在研究中并不是用于开放式闲聊，而是用于**结构化旅游评论分析任务**。如果更改提示词表述或维度顺序，输出效果可能与本研究结果不一致。
+
+### English
+
+To reproduce the behavior used in this research as closely as possible, please keep the original inference setup unchanged, including:
+
+1. the same system prompt  
+2. the same user prompt structure  
+3. the same order of the 11 evaluation dimensions  
+4. the exact same output format  
+5. the same inference parameters:
+   - `max_new_tokens=128`
+   - `do_sample=False`
+   - `num_beams=1`
+
+This model was not primarily designed for open-ended chatting. It was used for **structured tourism review analysis**. Changing the prompt wording or the dimension order may lead to outputs that differ from the results reported in the research. :contentReference[oaicite:1]{index=1}
+
+---
+
+## 调用代码示例：
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "dadaguai6677/TourismReview-Qwen2.5-7B"
+
+tokenizer = AutoTokenizer.from_pretrained(
+    model_id,
+    trust_remote_code=True,
+    padding_side="left"
+)
+
+if tokenizer.pad_token is None:
+    tokenizer.pad_token = tokenizer.eos_token
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.float16,
+    device_map="auto",
+    trust_remote_code=True,
+    low_cpu_mem_usage=True
+)
+
+model.eval()
+
+def create_prompt(text):
+    system_msg = "You are Qwen, created by Alibaba Cloud. You are a helpful assistant."
+    prompt = f"""<|im_start|>system
+{system_msg}<|im_end|>
+<|im_start|>user
+请对以下旅游评论进行内容分析，并基于以下11个维度进行打分。每个维度评分等级为1-5分，如未提及则返回null。
+
+评分标准：
+1分：完全不同意
+2分：不同意
+3分：一般
+4分：同意
+5分：完全同意
+null：未提及
+
+评价维度：
+放松惬意,乐趣满足,餐饮良好,购物丰富,娱乐活动多,交通便捷,服务友好,环境整洁,学习文化,体验工艺,家庭友好
+
+请严格按以下格式返回结果：
+放松惬意:分数,乐趣满足:分数,餐饮良好:分数,购物丰富:分数,娱乐活动多:分数,交通便捷:分数,服务友好:分数,环境整洁:分数,学习文化:分数,体验工艺:分数,家庭友好:分数
+
+待分析文本：
+{text}<|im_end|>
+<|im_start|>assistant
+"""
+    return prompt
+
+text = "景区环境很好，讲解也比较细致，孩子能学到很多历史文化知识，就是周边餐饮一般。"
+
+prompt = create_prompt(text)
+
+inputs = tokenizer(
+    prompt,
+    return_tensors="pt",
+    truncation=True,
+    max_length=1024,
+    padding=True
+).to(model.device)
+
+with torch.no_grad():
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=128,
+        do_sample=False,
+        pad_token_id=tokenizer.pad_token_id,
+        eos_token_id=tokenizer.eos_token_id,
+        num_beams=1
+    )
+
+full_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+if "<|im_start|>assistant" in full_text:
+    response = full_text.split("<|im_start|>assistant")[-1].strip()
+else:
+    response = full_text
+
+print(response)

added_tokens.json

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+{
+  "</tool_call>": 151658,
+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

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+{
+  "model_name": "tour-qwen2-7b-instruct",
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 3584,
+  "initializer_range": 0.02,
+  "intermediate_size": 18944,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 32768,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
+  "num_attention_heads": 28,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 4,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.56.2",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

generation_config.json

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+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "repetition_penalty": 1.05,
+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "4.56.2"
+}

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