初始化项目，由ModelHub XC社区提供模型

Model: Qwen/Qwen2-Math-7B
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- chat
+---
+
+
+# Qwen2-Math-7B
+
+> [!Warning]
+> <div align="center">
+> <b>
+> 🚨 Temporarily this model mainly supports English. We will release bilingual (English & Chinese) models soon!
+> </b>
+> </div>
+
+## Introduction
+
+Over the past year, we have dedicated significant effort to researching and enhancing the reasoning capabilities of large language models, with a particular focus on their ability to solve arithmetic and mathematical problems. Today, we are delighted to introduce a serise of math-specific large language models of our Qwen2 series,  Qwen2-Math and Qwen2-Math-Instruct-1.5B/7B/72B. Qwen2-Math is a series of specialized math language models built upon the Qwen2 LLMs, which significantly outperforms the mathematical capabilities of open-source models and even closed-source models (e.g., GPT4o). We hope that Qwen2-Math can contribute to the scientific community for solving advanced mathematical problems that require complex, multi-step logical reasoning.
+
+
+## Model Details
+
+
+For more details, please refer to our [blog post](https://qwenlm.github.io/blog/qwen2-math/) and [GitHub repo](https://github.com/QwenLM/Qwen2-Math).
+
+
+## Requirements
+* `transformers>=4.40.0` for Qwen2-Math models. The latest version is recommended.
+
+> [!Warning]
+> <div align="center">
+> <b>
+> 🚨 This is a must because `transformers` integrated Qwen2 codes since `4.37.0`.
+> </b>
+> </div>
+
+For requirements on GPU memory and the respective throughput, see similar results of Qwen2 [here](https://qwen.readthedocs.io/en/latest/benchmark/speed_benchmark.html).
+
+> [!Important]
+>
+> **Qwen2-Math-7B-Instruct** is an instruction model for chatting;
+>
+> **Qwen2-Math-7B** is a base model typically used for completion and few-shot inference, serving as a better starting point for fine-tuning.
+> 
+
+## Citation
+
+If you find our work helpful, feel free to give us a citation.
+
+```
+@article{yang2024qwen2,
+  title={Qwen2 technical report},
+  author={Yang, An and Yang, Baosong and Hui, Binyuan and Zheng, Bo and Yu, Bowen and Zhou, Chang and Li, Chengpeng and Li, Chengyuan and Liu, Dayiheng and Huang, Fei and others},
+  journal={arXiv preprint arXiv:2407.10671},
+  year={2024}
+}
+```

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 3584,
+  "initializer_range": 0.02,
+  "intermediate_size": 18944,
+  "max_position_embeddings": 4096,
+  "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_theta": 10000,
+  "sliding_window": 32768,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.44.0",
+  "use_cache": true,
+  "use_mrope": false,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

generation_config.json

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+  "do_sample": false,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.37.0"
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