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--- |
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license: other |
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license_name: deepseek |
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license_link: https://github.com/deepseek-ai/DeepSeek-Math/blob/main/LICENSE-MODEL |
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--- |
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<p align="center"> |
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<img width="500px" alt="DeepSeek Chat" src="https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/images/logo.png?raw=true"> |
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</p> |
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<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://chat.deepseek.com/">[🤖 Chat with DeepSeek LLM]</a> | <a href="https://discord.gg/Tc7c45Zzu5">[Discord]</a> | <a href="https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/images/qr.jpeg">[Wechat(微信)]</a> </p> |
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<p align="center"> |
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<a href="https://arxiv.org/pdf/2402.03300.pdf"><b>Paper Link</b>👁️</a> |
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</p> |
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<hr> |
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### 1. Introduction to DeepSeekMath |
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See the [Introduction](https://github.com/deepseek-ai/DeepSeek-Math) for more details. |
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### 2. How to Use |
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Here give some examples of how to use our model. |
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**Chat Completion** |
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❗❗❗ Please use chain-of-thought prompt to test DeepSeekMath-Instruct and DeepSeekMath-RL: |
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* English questions: `{question}\nPlease reason step by step, and put your final answer within \\boxed{}.` |
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* Chinese questions: `{question}\n请通过逐步推理来解答问题，并把最终答案放置于\\boxed{}中。` |
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```python |
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import torch |
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from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig |
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model_name = "deepseek-ai/deepseek-math-7b-instruct" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto") |
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model.generation_config = GenerationConfig.from_pretrained(model_name) |
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model.generation_config.pad_token_id = model.generation_config.eos_token_id |
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messages = [ |
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{"role": "user", "content": "what is the integral of x^2 from 0 to 2?\nPlease reason step by step, and put your final answer within \\boxed{}."} |
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] |
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input_tensor = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt") |
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outputs = model.generate(input_tensor.to(model.device), max_new_tokens=100) |
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result = tokenizer.decode(outputs[0][input_tensor.shape[1]:], skip_special_tokens=True) |
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print(result) |
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``` |
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Avoiding the use of the provided function `apply_chat_template`, you can also interact with our model following the sample template. Note that `messages` should be replaced by your input. |
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``` |
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User: {messages[0]['content']} |
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Assistant: {messages[1]['content']}<｜end▁of▁sentence｜>User: {messages[2]['content']} |
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Assistant: |
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``` |
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**Note:** By default (`add_special_tokens=True`), our tokenizer automatically adds a `bos_token` (`<｜begin▁of▁sentence｜>`) before the input text. Additionally, since the system prompt is not compatible with this version of our models, we DO NOT RECOMMEND including the system prompt in your input. |
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### 3. License |
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This code repository is licensed under the MIT License. The use of DeepSeekMath models is subject to the Model License. DeepSeekMath supports commercial use. |
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See the [LICENSE-MODEL](https://github.com/deepseek-ai/DeepSeek-Math/blob/main/LICENSE-MODEL) for more details. |
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### 4. Contact |
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If you have any questions, please raise an issue or contact us at [service@deepseek.com](mailto:service@deepseek.com). |
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