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Model: FoolBird/Qwen-2.5-1.5b-instruct-JZFH
Source: Original Platform

.gitattributes

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README.md

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+---
+license: Apache License 2.0
+
+#model-type:
+##如 gpt、phi、llama、chatglm、baichuan 等
+#- gpt
+
+#domain:
+##如 nlp、cv、audio、multi-modal
+#- nlp
+
+#language:
+##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
+#- cn
+
+#metrics:
+##如 CIDEr、Blue、ROUGE 等
+#- CIDEr
+
+#tags:
+##各种自定义，包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
+#- pretrained
+
+#tools:
+##如 vllm、fastchat、llamacpp、AdaSeq 等
+#- vllm
+language:
+  - zh
+tasks:
+  - text-generation
+frameworks: PyTorch
+base_model:
+  - Qwen/Qwen2.5-1.5B-Instruct
+---
+### 本模型是用数据集FoolBird/GB50016-2014对Qwen2.5-1.5B-Instruct进行预训练，训练轮数250轮
+### 数据集地址https://modelscope.cn/datasets/FoolBird/GB50016-2014
+### 本模型仅供学习使用
+#### 您可以通过如下git clone命令，或者ModelScope SDK来下载模型
+
+SDK下载
+```bash
+#安装ModelScope
+pip install modelscope
+```
+```python
+#SDK模型下载
+from modelscope import snapshot_download
+model_dir = snapshot_download('FoolBird/Qwen-2.5-1.5b-instruct-JZFH')
+```
+Git下载
+```
+#Git模型下载
+git clone https://www.modelscope.cn/FoolBird/Qwen-2.5-1.5b-instruct-JZFH.git
+```
+使用本模型进行推理
+```python
+# 使用本模型进行推理
+from vllm import LLM, SamplingParams
+import os
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from modelscope import snapshot_download
+import torch
+import time
+
+# 调用 ModelScope 模型
+model_id = 'FoolBird/Qwen-2.5-1.5b-instruct-JZFH'  # ModelScope 上的模型 ID
+
+# 初始化全局变量
+llm = None
+tokenizer = None
+sampling_params = None
+
+# 下载 ModelScope 模型
+def download_modelscope_model(model_id):
+    # 下载模型并返回本地路径
+    model_path = snapshot_download(model_id)
+    return model_path
+
+# 初始化模型和 tokenizer
+def qwen_vllm(model_path):
+    # 设置 CUDA 设备为 GPU 2
+    os.environ["CUDA_VISIBLE_DEVICES"] = "0"
+
+    global llm, tokenizer
+    sum = 1
+
+    # 设置 CUDA 设备为 GPU 2 (在设置的上下文中，它是索引0)
+    torch.cuda.set_device(0)
+
+    # 加载模型
+    llm = LLM(model=model_path, tensor_parallel_size=sum, dtype=torch.float16, enforce_eager=True, gpu_memory_utilization=0.8, max_model_len=1024)
+    tokenizer = AutoTokenizer.from_pretrained(model_path)
+    text = "qwen_vllm加载完毕"
+    print(text)
+    return text
+
+# 使用 VLLM 进行推理
+def qwen2_5_inference(info):
+    messages = [
+        {"role": "system", "content":' You are Qwen, created by Alibaba Cloud. You are a helpful assistant'},
+        {"role": "user", "content": info}
+    ]
+
+    # 聊天模板的消息
+    text = tokenizer.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True
+    )
+
+    # 清理未使用的显存
+    torch.cuda.empty_cache()
+
+    global sampling_params
+
+     
+    sampling_params = SamplingParams(temperature=0.7, top_p=0.8, repetition_penalty=1.05, max_tokens=512)
+    outputs = llm.generate([text], sampling_params)
+
+    # 流式输出结果
+    for output in outputs:
+        generated_text = output.outputs[0].text
+        for char in generated_text:
+            print(char, end='', flush=True)  # 流式输出每个字符
+            time.sleep(0.05) 
+
+if __name__ == '__main__':
+    model_path = download_modelscope_model(model_id)
+    qwen_vllm(model_path)
+    while True:
+        user_input = input("请输入您的问题: ")
+        qwen2_5_inference(user_input)
+        print(" ")
+        
+        
+        # 清理未使用的显存
+        torch.cuda.empty_cache()
+```

added_tokens.json

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+  "<tool_call>": 151657,
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+}

config.json

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+{
+  "_name_or_path": "Qwen/Qwen2.5-1.5B",
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 1536,
+  "initializer_range": 0.02,
+  "intermediate_size": 8960,
+  "max_position_embeddings": 131072,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 2,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.45.2",
+  "use_cache": true,
+  "use_mrope": false,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

configuration.json

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+{"framework": "pytorch", "task": "other"}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.45.2"
+}

model.safetensors

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+oid sha256:1043db3035892339142cf2b103fa0056424bfb3120023dde32aaed486b2902ce
+size 3087467144

special_tokens_map.json

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+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
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+    "<|quad_start|>",
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+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
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+      "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,
+  "chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% endif %}{% if system_message is defined %}{{ system_message + '\n' }}{% endif %}{% for message in loop_messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ 'Human: ' + content + '\nAssistant:' }}{% elif message['role'] == 'assistant' %}{{ content + '<|endoftext|>' + '\n' }}{% endif %}{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

upload.py

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+from modelscope.hub.api import HubApi
+
+YOUR_ACCESS_TOKEN = '672c3a5a-4b18-4e97-b557-8b71c443b4f4'
+api = HubApi()
+api.login(YOUR_ACCESS_TOKEN)
+
+# 1. 创建模型库
+from modelscope.hub.constants import Licenses, ModelVisibility
+
+username = 'FoolBird'
+model_name = 'Qwen-2.5-1.5b-instruct-JZFH'
+model_id=f"{username}/{model_name}"
+
+api.create_model(
+    model_id,
+    visibility=ModelVisibility.PUBLIC,
+    license=Licenses.APACHE_V2,
+    chinese_name="千问2.5-1.5B-建筑防火规范",
+)
+
+# # 2. 上传模型文件
+
+# api.push_model(
+#     model_id=model_id, # 如果model_id对应的模型库不存在，将会被自动创建
+#     model_dir="D:\PythonProject\output", # 指定本地模型所在目录
+#     revision='new_branch'  # 更改分支名称
+# )