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Model: wuyonghui0810/text-generation Source: Original Platform
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runs/
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README.md
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---
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license: Apache License 2.0
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language:
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- zh
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tasks:
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- text-generation
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frameworks: PyTorch
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base_model:
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- Qwen/Qwen2.5-0.5B-Instruct
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base_model_relation: finetune
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widgets:
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- version: 1
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task: text-generation
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inputs:
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- type: text
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displayType: TextArea
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validator:
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max_words: 128
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output:
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displayType: Text
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displayValueMapping: text
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examples:
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- name: 1
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title: 示例1
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inputs:
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- name: text
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data: 光的速度是多少?
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datasets:
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- wuyonghui0810/General-Knowledge
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tags:
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- 文本生成
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- 科技探索
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- ' 永辉'
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---
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# Qwen2.5-0.5B-Instruct 微调模型
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## 模型概述
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这是一个基于 Qwen2.5-0.5B-Instruct 模型的微调版本，使用 LoRA (低秩适应) 训练方法在特定领域数据上进行了定制化训练，涵盖数学、英语、科学、化学、物理等1000条自定义数据进行训练，以增强模型在特定任务上的性能。
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## 模型详情
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- **基础模型**: Qwen/Qwen2.5-0.5B-Instruct
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- **模型类型**: qwen2_5
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- **训练方法**: LoRA 微调
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- **模板**: qwen2_5
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- **模型大小**: 0.5B 参数
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- **检查点**: checkpoint-186-merged
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- **训练日期**: 2025-08-05
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## 训练配置
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- **最大序列长度**: 1024 个 token
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- **学习率**: 1e-4
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- **梯度累积步数**: 16
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- **训练轮数**: 3
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- **最终训练损失**: 0.0802
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- **最终评估损失**: 0.00013508
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## 调用方法
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### 快速开始
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这里提供了一个使用 wuyonghui0810/text-generation模型的代码片段，展示了如何加载分词器和模型以及如何生成内容。
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```python
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from modelscope import AutoModelForCausalLM, AutoTokenizer
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model_name = "wuyonghui0810/text-generation"
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype="auto",
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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prompt = "光的速度是多少?"
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messages = [
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{"role": "system", "content": "You are Vkey, created by yonghui, You are a helpful assistant."},
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{"role": "user", "content": prompt}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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generated_ids = model.generate(
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**model_inputs,
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max_new_tokens=512
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)
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generated_ids = [
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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]
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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print(response)
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```
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### 训练前
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光的传播速度是多少：
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- 在标准条件下，光的传播速度约为 299792458 米/秒。这个速度是恒定不变的，无论光源的位置、距离多远，都保持不变。这与物理定律和实验数据一致，证明了光速是宇宙中的基本物理常数。
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### 训练后
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- <<< 光的传播速度是多少
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- <think>
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- 用户问的是关于物理的问题：'光的传播速度是多少'。我需要根据物理学原理给出准确的答案。对于这个问题，正确的回答是：光在真空中的传播速度约为299,792,458米/秒。。
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- </think>
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- <answer>
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- 光在真空中的传播速度约为299,792,458米/秒。
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- </answer>
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- <<< 光的速度
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- <think>
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- 用户问的是关于物理的问题：'光的速度'。我需要根据物理学原理给出准确的答案。对于这个问题，正确的回答是：光在真空中的速度约为299,792,458米/秒。。
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- </think>
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- <answer>
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- 光在真空中的速度约为299,792,458米/秒。
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- </answer>
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## 微调方法
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### 使用 Swift 进行训练认知微调
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```bash
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CUDA_VISIBLE_DEVICES=0 \
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swift sft \
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--torch_dtype 'float16' \
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--model 'Qwen/Qwen2.5-0.5B-Instruct' \
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--model_type 'qwen2_5' \
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--template 'qwen2_5' \
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--system 'You are Vkey, created by yonghui. You are a helpful assistant.' \
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--dataset '/mnt/workspace/myipynb/transformers/datasets/training_data.jsonl' \
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--max_length '1024' \
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--init_weights 'True' \
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--learning_rate '1e-4' \
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--gradient_accumulation_steps '16' \
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--eval_steps '500' \
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--truncation_strategy 'delete' \
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--report_to 'tensorboard' \
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--add_version False \
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--output_dir /mnt/workspace/myipynb/transformers/ms-swift/output/Qwen2.5-0.5B-Instruct/v0-20250805-170718 \
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--logging_dir /mnt/workspace/myipynb/transformers/ms-swift/output/Qwen2.5-0.5B-Instruct/v0-20250805-170718/runs \
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--ignore_args_error True \
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--device_map 'cpu' \
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> /mnt/workspace/myipynb/transformers/ms-swift/output/Qwen2.5-0.5B-Instruct/v0-20250805-170718/runs/run.log 2>&1 &
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```
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### 使用 swift 框架进行推理
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||||
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||||
```bash
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CUDA_VISIBLE_DEVICES=0 \
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swift infer \
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--model /mnt/workspace/myipynb/transformers/ms-swift/output/Qwen2.5-0.5B-Instruct/v0-20250805-170718/checkpoint-186-merged \
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||||
--merge_lora true \
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||||
--infer_backend vllm \
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||||
--temperature 0 \
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||||
--max_new_tokens 2048
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||||
```
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### 使用 swift 框架进行导出
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||||
--adapters 参数：用于导出适配器权重（如 LoRA），需要配合基础模型使用
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||||
--model 参数：用于导出完整模型，可以直接使用
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||||
由于 checkpoint-186-merged 是一个完整的合并模型（包含基础模型和适配器权重），所以应该使用 --model 参数。
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||||
|
||||
方案一（使用的这个）：
|
||||
```bash
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||||
CUDA_VISIBLE_DEVICES=0 swift export \
|
||||
--model /mnt/workspace/myipynb/transformers/ms-swift/output/Qwen2.5-0.5B-Instruct/v0-20250805-170718/checkpoint-186-merged \
|
||||
--push_to_hub true \
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||||
--hub_model_id 'wuyonghui0810/text-generation' \
|
||||
--hub_token 'ms-c9f5013e-8343-4d26-a53b-4d5a75f8a973' \
|
||||
--use_hf false
|
||||
```
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||||
|
||||
方案二：
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||||
```bash
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||||
CUDA_VISIBLE_DEVICES=0 swift export \
|
||||
--adapters /mnt/workspace/myipynb/transformers/ms-swift/output/Qwen2.5-0.5B-Instruct/v0-20250805-170718/checkpoint-186 \
|
||||
--push_to_hub true \
|
||||
--hub_model_id 'wuyonghui0810/text-generation' \
|
||||
--hub_token 'ms-c9f5013e-8343-4d26-a53b-4d5a75f8a973' \
|
||||
--use_hf false
|
||||
```
|
||||
|
||||
### 关键推理参数
|
||||
|
||||
- `--model`: 用于导出完整模型，可以直接使用（或者--adapters：训练好的适配器/LoRA 权重路径）
|
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- `--merge_lora true`: 将 LoRA 权重与基础模型合并
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||||
- `--infer_backend vllm`: 使用 vLLM 进行推理加速
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||||
- `--temperature 0`: 确定性输出（贪婪解码）
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||||
- `--max_new_tokens 2048`: 最大生成 token 数量
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||||
|
||||
## 性能表现
|
||||
|
||||
- **评估样本每秒处理数**: 18.64
|
||||
- **训练样本每秒处理数**: 5.045
|
||||
- **内存使用**: 模型权重约 0.9276 GB
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||||
- **推理速度**: 使用 vLLM 和 CUDA 图形优化
|
||||
|
||||
## 系统要求
|
||||
|
||||
- **GPU**: 支持 CUDA 的 GPU（推荐）
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||||
- **显存**: 至少 4-8GB 以获得最佳性能
|
||||
- **软件环境**:
|
||||
- Python 3.11+
|
||||
- Swift 框架
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||||
- vLLM 库
|
||||
- CUDA 工具包
|
||||
|
||||
## 模型能力
|
||||
此微调模型设计用于：
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||||
|
||||
- 回答特定领域问题
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||||
- 准确遵循指令
|
||||
- 提供一致且确定性的响应（temperature=0时）
|
||||
- 处理长上下文输入（最多8192个token）
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||||
|
||||
## 局限性
|
||||
- 当 temperature=0 时响应是确定性的
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- 性能取决于微调数据的质量
|
||||
- 在训练领域外可能泛化能力有限
|
||||
|
||||
*如需技术支持或有关此模型的问题，请参考模型目录中包含的训练日志和配置文件。*
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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,
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"<|image_pad|>": 151655,
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"<|object_ref_end|>": 151647,
|
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"<|object_ref_start|>": 151646,
|
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"<|quad_end|>": 151651,
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"<|quad_start|>": 151650,
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"<|repo_name|>": 151663,
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"<|video_pad|>": 151656,
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"<|vision_end|>": 151653,
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"<|vision_pad|>": 151654,
|
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"<|vision_start|>": 151652
|
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}
|
||||
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 %}
|
||||
55
config.json
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config.json
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||||
{
|
||||
"architectures": [
|
||||
"Qwen2ForCausalLM"
|
||||
],
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151645,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 896,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 4864,
|
||||
"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"
|
||||
],
|
||||
"max_position_embeddings": 32768,
|
||||
"max_window_layers": 21,
|
||||
"model_type": "qwen2",
|
||||
"num_attention_heads": 14,
|
||||
"num_hidden_layers": 24,
|
||||
"num_key_value_heads": 2,
|
||||
"pad_token_id": 151643,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 1000000.0,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.53.1",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
1
configuration.json
Normal file
1
configuration.json
Normal file
@@ -0,0 +1 @@
|
||||
{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
|
||||
14
generation_config.json
Normal file
14
generation_config.json
Normal file
@@ -0,0 +1,14 @@
|
||||
{
|
||||
"bos_token_id": 151643,
|
||||
"do_sample": true,
|
||||
"eos_token_id": [
|
||||
151645,
|
||||
151643
|
||||
],
|
||||
"pad_token_id": 151643,
|
||||
"repetition_penalty": 1.1,
|
||||
"temperature": 0.7,
|
||||
"top_k": 20,
|
||||
"top_p": 0.8,
|
||||
"transformers_version": "4.53.1"
|
||||
}
|
||||
151388
merges.txt
Normal file
151388
merges.txt
Normal file
File diff suppressed because it is too large
Load Diff
3
model.safetensors
Normal file
3
model.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:a9f1b2323d74724e6cde2ee2f1181e7dee168aae2094343497b6c4d461dce11a
|
||||
size 988097824
|
||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"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|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
757444
tokenizer.json
Normal file
757444
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
207
tokenizer_config.json
Normal file
207
tokenizer_config.json
Normal file
@@ -0,0 +1,207 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"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|>",
|
||||
"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