初始化项目，由ModelHub XC社区提供模型
Model: eshmoideas/Qwen2-Math Source: Original Platform
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README.md
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---
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license: apache-2.0
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language:
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- en
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pipeline_tag: text-generation
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tags:
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- chat
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---
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# Qwen2-Math-7B-Instruct
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> [!Warning]
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> <div align="center">
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> <b>
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> 🚨 Temporarily this model mainly supports English. We will release bilingual (English & Chinese) models soon!
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> </b>
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> </div>
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## Introduction
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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.
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## Model Details
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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).
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## Requirements
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* `transformers>=4.40.0` for Qwen2-Math models. The latest version is recommended.
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> [!Warning]
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> <div align="center">
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> <b>
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> 🚨 This is a must because `transformers` integrated Qwen2 codes since `4.37.0`.
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> </b>
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> </div>
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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).
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## Quick Start
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> [!Important]
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>
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> **Qwen2-Math-7B-Instruct** is an instruction model for chatting;
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>
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> **Qwen2-Math-7B** is a base model typically used for completion and few-shot inference, serving as a better starting point for fine-tuning.
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>
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### 🤗 Hugging Face Transformers
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Qwen2-Math can be deployed and inferred in the same way as [Qwen2](https://github.com/QwenLM/Qwen2). Here we show a code snippet to show you how to use the chat model with `transformers`:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "Qwen/Qwen2-Math-7B-Instruct"
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device = "cuda" # the device to load the model onto
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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 = "Find the value of $x$ that satisfies the equation $4x+5 = 6x+7$."
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messages = [
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{"role": "system", "content": "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(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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```
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### 🤖 ModelScope
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We strongly advise users, especially those in mainland China, to use ModelScope. `snapshot_download` can help you solve issues concerning downloading checkpoints.
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## Citation
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If you find our work helpful, feel free to give us a citation.
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```
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@article{yang2024qwen2,
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title={Qwen2 technical report},
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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},
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journal={arXiv preprint arXiv:2407.10671},
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year={2024}
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}
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```
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config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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"hidden_act": "silu",
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"hidden_size": 3584,
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"initializer_range": 0.02,
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"intermediate_size": 18944,
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"max_position_embeddings": 4096,
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"max_window_layers": 28,
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"model_type": "qwen2",
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"num_attention_heads": 28,
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"num_hidden_layers": 28,
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"num_key_value_heads": 4,
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"rms_norm_eps": 1e-06,
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"rope_theta": 10000.0,
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"sliding_window": 32768,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.43.1",
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"use_cache": true,
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"use_mrope": false,
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"use_sliding_window": false,
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"vocab_size": 152064
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}
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}
|
||||
}
|
||||
303111
tokenizer.json
Normal file
303111
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
40
tokenizer_config.json
Normal file
40
tokenizer_config.json
Normal file
@@ -0,0 +1,40 @@
|
||||
{
|
||||
"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": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"model_max_length": 32768,
|
||||
"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