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Model: dadaguai6677/TourismReview-Qwen2.5-7B Source: Original Platform
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Modelfile
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Modelfile
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# ollama modelfile auto-generated by llamafactory
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FROM .
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TEMPLATE """{{ if .System }}<|im_start|>system
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{{ .System }}<|im_end|>
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||||
{{ end }}{{ range .Messages }}{{ if eq .Role "user" }}<|im_start|>user
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{{ .Content }}<|im_end|>
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<|im_start|>assistant
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{{ else if eq .Role "assistant" }}{{ .Content }}<|im_end|>
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{{ end }}{{ end }}"""
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|
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SYSTEM """You are Qwen, created by Alibaba Cloud. You are a helpful assistant."""
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PARAMETER stop "<|im_end|>"
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PARAMETER num_ctx 4096
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210
README.md
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210
README.md
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---
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language:
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- zh
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- en
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license: apache-2.0
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- tourism
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- cultural-heritage
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- review-analysis
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- qwen2
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- lora
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- chinese
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base_model: Qwen/Qwen2.5-7B-Instruct
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model_name: TourismReview-Qwen2.5-7B
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---
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# TourismReview-Qwen2.5-7B
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## 中文介绍
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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。
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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。
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本仓库发布的模型名称为：
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**`dadaguai6677/TourismReview-Qwen2.5-7B`**
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|
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---
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## English Introduction
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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.
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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.
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The released repository name is:
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||||
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||||
**`dadaguai6677/TourismReview-Qwen2.5-7B`**
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||||
|
||||
---
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||||
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||||
# 模型信息 | Model Details
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## 中文
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||||
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- **模型名称**：TourismReview-Qwen2.5-7B
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- **基础模型**：Qwen/Qwen2.5-7B-Instruct
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- **模型架构**：Qwen2ForCausalLM
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- **任务类型**：文本生成 / 评论分析 / 多维评分
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- **适用语言**：中文为主，兼容英文说明
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||||
- **应用方向**：旅游评论分析、文化遗产旅游研究、游客感知评价
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## English
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||||
- **Model Name**: TourismReview-Qwen2.5-7B
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- **Base Model**: Qwen/Qwen2.5-7B-Instruct
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- **Architecture**: Qwen2ForCausalLM
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- **Task Type**: Text generation / Review analysis / Multi-dimensional scoring
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- **Primary Language**: Chinese, with English documentation support
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- **Domain**: Tourism review analysis, cultural heritage tourism research, visitor perception evaluation
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||||
---
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||||
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||||
# 适用任务 | Intended Use
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||||
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||||
## 中文
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||||
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||||
本模型适用于以下任务：
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||||
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||||
- 旅游评论内容分析
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||||
- 游客感知价值识别
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||||
- 文化遗产旅游体验评价
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||||
- 多维文本结构化打分
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||||
- 旅游研究中的辅助编码与大规模文本处理
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||||
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||||
## English
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||||
|
||||
This model is intended for:
|
||||
|
||||
- tourism review content analysis
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||||
- visitor perceived value assessment
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||||
- cultural heritage tourism experience evaluation
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||||
- structured multi-dimensional scoring
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||||
- large-scale text processing for tourism research
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||||
|
||||
---
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||||
|
||||
# 使用方法 | How to Use
|
||||
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||||
## 重要说明（请务必阅读）| Important Note
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||||
|
||||
### 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
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||||
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}
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||||
|
||||
---
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||||
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||||
## 调用代码示例：
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||||
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||||
```python
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||||
import torch
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||||
from transformers import AutoModelForCausalLM, AutoTokenizer
|
||||
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||||
model_id = "dadaguai6677/TourismReview-Qwen2.5-7B"
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||||
tokenizer = AutoTokenizer.from_pretrained(
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||||
model_id,
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||||
trust_remote_code=True,
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||||
padding_side="left"
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||||
)
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||||
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||||
if tokenizer.pad_token is None:
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||||
tokenizer.pad_token = tokenizer.eos_token
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||||
|
||||
model = AutoModelForCausalLM.from_pretrained(
|
||||
model_id,
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||||
torch_dtype=torch.float16,
|
||||
device_map="auto",
|
||||
trust_remote_code=True,
|
||||
low_cpu_mem_usage=True
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||||
)
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||||
model.eval()
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||||
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||||
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
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||||
3分：一般
|
||||
4分：同意
|
||||
5分：完全同意
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||||
null：未提及
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||||
|
||||
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)
|
||||
24
added_tokens.json
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added_tokens.json
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{
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"</tool_call>": 151658,
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"<tool_call>": 151657,
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"<|box_end|>": 151649,
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"<|box_start|>": 151648,
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"<|endoftext|>": 151643,
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"<|file_sep|>": 151664,
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"<|fim_middle|>": 151660,
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"<|fim_pad|>": 151662,
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"<|fim_prefix|>": 151659,
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"<|fim_suffix|>": 151661,
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"<|im_end|>": 151645,
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||||
"<|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
|
||||
}
|
||||
54
chat_template.jinja
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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 %}
|
||||
59
config.json
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59
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
|
||||
}
|
||||
14
generation_config.json
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14
generation_config.json
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|
||||
{
|
||||
"bos_token_id": 151643,
|
||||
"do_sample": true,
|
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"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user