马 仕镕
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README.md
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license: other
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license_name: deepseek
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license_link: LICENSE
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---
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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-V2/blob/main/LICENSE-MODEL
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---
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<!-- markdownlint-disable first-line-h1 -->
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<!-- markdownlint-disable html -->
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<!-- markdownlint-disable no-duplicate-header -->
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<div align="center">
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<img src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/logo.svg?raw=true" width="60%" alt="DeepSeek-V2" />
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</div>
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<hr>
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<div align="center" style="line-height: 1;">
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<a href="https://www.deepseek.com/" target="_blank" style="margin: 2px;">
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<img alt="Homepage" src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/badge.svg?raw=true" style="display: inline-block; vertical-align: middle;"/>
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</a>
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<a href="https://chat.deepseek.com/" target="_blank" style="margin: 2px;">
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<img alt="Chat" src="https://img.shields.io/badge/🤖%20Chat-DeepSeek%20V2-536af5?color=536af5&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
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</a>
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<a href="https://huggingface.co/deepseek-ai" target="_blank" style="margin: 2px;">
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<img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-DeepSeek%20AI-ffc107?color=ffc107&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
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</a>
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</div>
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<div align="center" style="line-height: 1;">
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<a href="https://discord.gg/Tc7c45Zzu5" target="_blank" style="margin: 2px;">
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<img alt="Discord" src="https://img.shields.io/badge/Discord-DeepSeek%20AI-7289da?logo=discord&logoColor=white&color=7289da" style="display: inline-block; vertical-align: middle;"/>
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</a>
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<a href="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/qr.jpeg?raw=true" target="_blank" style="margin: 2px;">
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<img alt="Wechat" src="https://img.shields.io/badge/WeChat-DeepSeek%20AI-brightgreen?logo=wechat&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
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</a>
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<a href="https://twitter.com/deepseek_ai" target="_blank" style="margin: 2px;">
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<img alt="Twitter Follow" src="https://img.shields.io/badge/Twitter-deepseek_ai-white?logo=x&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
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</a>
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</div>
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<div align="center" style="line-height: 1;">
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<a href="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/LICENSE-CODE" style="margin: 2px;">
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<img alt="Code License" src="https://img.shields.io/badge/Code_License-MIT-f5de53?&color=f5de53" style="display: inline-block; vertical-align: middle;"/>
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</a>
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<a href="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/LICENSE-MODEL" style="margin: 2px;">
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<img alt="Model License" src="https://img.shields.io/badge/Model_License-Model_Agreement-f5de53?&color=f5de53" style="display: inline-block; vertical-align: middle;"/>
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</a>
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</div>
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<p align="center">
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<a href="#2-model-downloads">Model Download</a> |
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<a href="#3-evaluation-results">Evaluation Results</a> |
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<a href="#4-model-architecture">Model Architecture</a> |
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<a href="#6-api-platform">API Platform</a> |
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<a href="#8-license">License</a> |
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<a href="#9-citation">Citation</a>
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</p>
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<p align="center">
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<a href="https://arxiv.org/abs/2405.04434"><b>Paper Link</b>👁️</a>
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</p>
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# DeepSeek-V2-Chat-0628
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## 1. Introduction
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DeepSeek-V2-Chat-0628 is an improved version of DeepSeek-V2-Chat. For model details, please visit [DeepSeek-V2 page](https://huggingface.co/deepseek-ai/DeepSeek-V2-Chat) for more information.
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DeepSeek-V2-Chat-0628 has achieved remarkable performance on the LMSYS Chatbot Arena Leaderboard:
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- Overall Ranking: #11, outperforming all other open-source models.
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- Coding Arena Ranking: #3, showcasing exceptional capabilities in coding tasks.
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- Hard Prompts Arena Ranking: #3, demonstrating strong performance on challenging prompts.
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<p align="center">
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<img width="90%" src="figures/arena1.png" />
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</p>
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<p align="center">
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<img width="90%" src="figures/arena2.png" />
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</p>
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## 2. Improvement
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Compared to the previous version DeepSeek-V2-Chat, the new version has made the following improvements:
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- Code: HumanEval Pass@1 increased from 79.88% to 84.76%.
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- Mathematics: MATH ACC@1 improved from 55.02% to 71.02%.
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- Reasoning: Big-Bench-Hard(BBH) improved from 78.56% to 83.40%.
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- Instruction Following: IFEval Benchmark Prompt-Level accuracy improved from 63.9% to 77.6%.
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- JSON Format Output: Internal test set performance increased from 78% to 85%.
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- Additionally, in the Arena-Hard evaluation, the win rate against GPT-4-0314 has increased from 41.6% to 68.3%. Furthermore, the instruction following capability in the "system" area has been optimized, significantly enhancing the user experience for immersive translation, RAG, and other tasks.
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## 3. How to run locally
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**To utilize DeepSeek-V2-Chat-0628 in BF16 format for inference, 80GB*8 GPUs are required.**
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### Inference with Huggingface's Transformers
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You can directly employ [Huggingface's Transformers](https://github.com/huggingface/transformers) for model inference.
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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-V2-Chat-0628"
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tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
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# `max_memory` should be set based on your devices
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max_memory = {i: "75GB" for i in range(8)}
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# `device_map` cannot be set to `auto`
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model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True, device_map="sequential", torch_dtype=torch.bfloat16, max_memory=max_memory, attn_implementation="eager")
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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": "Write a piece of quicksort code in C++"}
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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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The complete chat template can be found within `tokenizer_config.json` located in the huggingface model repository.
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**Note: The chat template has been updated compared to the previous DeepSeek-V2-Chat version.**
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An example of chat template is as belows:
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```bash
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<|begin▁of▁sentence|><|User|>{user_message_1}<|Assistant|>{assistant_message_1}<|end▁of▁sentence|><|User|>{user_message_2}<|Assistant|>
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```
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You can also add an optional system message:
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```bash
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<|begin▁of▁sentence|>{system_message}
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<|User|>{user_message_1}<|Assistant|>{assistant_message_1}<|end▁of▁sentence|><|User|>{user_message_2}<|Assistant|>
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```
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### Inference with vLLM (recommended)
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To utilize [vLLM](https://github.com/vllm-project/vllm) for model inference, please merge this Pull Request into your vLLM codebase: https://github.com/vllm-project/vllm/pull/4650.
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```python
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from transformers import AutoTokenizer
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from vllm import LLM, SamplingParams
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max_model_len, tp_size = 8192, 8
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model_name = "deepseek-ai/DeepSeek-V2-Chat-0628"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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llm = LLM(model=model_name, tensor_parallel_size=tp_size, max_model_len=max_model_len, trust_remote_code=True, enforce_eager=True)
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sampling_params = SamplingParams(temperature=0.3, max_tokens=256, stop_token_ids=[tokenizer.eos_token_id])
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messages_list = [
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[{"role": "user", "content": "Who are you?"}],
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[{"role": "user", "content": "Translate the following content into Chinese directly: DeepSeek-V2 adopts innovative architectures to guarantee economical training and efficient inference."}],
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[{"role": "user", "content": "Write a piece of quicksort code in C++."}],
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]
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prompt_token_ids = [tokenizer.apply_chat_template(messages, add_generation_prompt=True) for messages in messages_list]
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outputs = llm.generate(prompt_token_ids=prompt_token_ids, sampling_params=sampling_params)
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generated_text = [output.outputs[0].text for output in outputs]
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print(generated_text)
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```
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## 4. License
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This code repository is licensed under [the MIT License](LICENSE-CODE). The use of DeepSeek-V2 Base/Chat models is subject to [the Model License](LICENSE-MODEL). DeepSeek-V2 series (including Base and Chat) supports commercial use.
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## 5. Citation
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```
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@misc{deepseekv2,
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title={DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model},
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author={DeepSeek-AI},
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year={2024},
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eprint={2405.04434},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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## 6. Contact
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If you have any questions, please raise an issue or contact us at [[email protected]]([email protected]).
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figures/arena2.png
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