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+ Quantization made by Sudhanshu Sharma.
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+ [Github](https://github.com/sudhanshu746)
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+ deepseek-math-7b-rl - bnb 4bits
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+ - Model creator: https://huggingface.co/deepseek-ai/
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+ - Original model: https://huggingface.co/deepseek-ai/deepseek-math-7b-rl/
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+ Original model description:
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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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