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Model: qsddfxcxx/Process-Thinking-1.5B
Source: Original Platform

.gitattributes

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+*.llamafile* filter=lfs diff=lfs merge=lfs -text
+*.pt2 filter=lfs diff=lfs merge=lfs -text

README.md

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+## 介绍
+
+智辰流程优化模型，作为一款搭载了15亿参数的先进系统，其利用Qwen2模型的核心架构进行设计，旨在深度剖析并优化各类复杂业务流程。该模型通过精细化的学习与调整，能够输出高度贴合实际业务场景的操作流程建议，极大地提升了决策效率与执行精准度。
+
+目前，智辰流程优化模型已广泛吸纳了电商运营、新媒体内容创作、直播营销、创业就业指导以及软件设计等多个领域的海量训练数据，这些数据为模型提供了丰富的业务场景案例与经验积累。特别是在电商与新媒体领域，模型展现出了卓越的适应性与优化能力；而在直播与创业就业方面，其分析也颇具洞见；尽管在软件设计领域的优化效果尚显平稳，但已展现出巨大的潜力与提升空间。
+
+## Process-Thinking-1.5B
+Process-Thinking模型主要特点有：
+
+    1.流程思考：深度思考，根据用户输入业务，拆分其业务流程，输出内容主要为业务流程的充分结果（部分业务仍需添加流程等关键词）。
+    2.推理成本低：本模型本地部署推理时使用显存在3GB左右，可支持微调，微调使用显存约为6GB。
+
+## 训练细节
+
+本模型使用电商运营、新媒体内容创作、直播营销、创业就业指导以及软件设计等多个领域的海量训练数据进行后训练，用户使用版本是聊天模型。
+
+## 环境要求
+
+我们建议安装 transformers>=4.37.0，如果使用GPU加速推理，建议检查好CUDA等环境是否配置完成。
+
+## 模型使用
+
+```python
+from modelscope import AutoModelForCausalLM, AutoTokenizer
+device = "cuda" # 启用CUDA
+
+model = AutoModelForCausalLM.from_pretrained(
+    "qsddfxcxx/Process-Thinking-1.5B",
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained("qsddfxcxx/Process-Thinking-1.5B") # 模型配置注意名称是否正确
+
+prompt = "AI软件开发"
+messages = [
+    {"role": "system", "content": "你是一个助手"},
+    {"role": "user", "content": prompt}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+model_inputs = tokenizer([text], return_tensors="pt").to(device)
+
+generated_ids = model.generate(
+    model_inputs.input_ids,
+    max_new_tokens=1024
+)
+generated_ids = [
+    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
+
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+print(response) # 也可下载模型至本地，利用Ollama、LM Studio等工具进行大模型问答
+```
+
+## 使用结果截图
+
+![alt text](https://www.modelscope.cn/api/v1/models/qsddfxcxx/Process-Thinking-1.5B/repo?Revision=master&FilePath=%E6%95%88%E6%9E%9C.jpg&View=true)
+
+## 模型下载
+
+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('qsddfxcxx/Process-Thinking-1.5B')
+```
+Git下载
+```
+#Git模型下载
+git clone https://www.modelscope.cn/qsddfxcxx/Process-Thinking-1.5B.git
+```
+
+<p style="color: lightgrey;">如果您是本模型的贡献者，我们邀请您根据<a href="https://modelscope.cn/docs/ModelScope%E6%A8%A1%E5%9E%8B%E6%8E%A5%E5%85%A5%E6%B5%81%E7%A8%8B%E6%A6%82%E8%A7%88" style="color: lightgrey; text-decoration: underline;">模型贡献文档</a></p>

added_tokens.json

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+{
+  "<|endoftext|>": 151643,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644
+}

config.json

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+{
+  "_name_or_path": "D:\\llamafac\\models",
+  "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_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.43.4",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

configuration.json

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+{"framework":"Pytorch","task":"text-generation"}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.43.4"
+}

model.safetensors

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+size 3087467144

special_tokens_map.json

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+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "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_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
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "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": 32768,
+  "pad_token": "<|endoftext|>",
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}