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https://github.com/deepseek-ai/DeepSeek-V2/blob/main/LICENSE-MODEL +--- + +GGUF version made with [llama.cpp 705b7ec](https://github.com/ggerganov/llama.cpp/commit/705b7ecf60e667ced57c15d67aa86865e3cc7aa7) + +Original model [deepseek-ai/DeepSeek-V2-Chat-0628](https://huggingface.co/deepseek-ai/DeepSeek-V2-Chat-0628) + + + + + +
+ DeepSeek-V2 +
+
+
+ + Homepage + + + Chat + + + Hugging Face + +
+ +
+ + Discord + + + Wechat + + + Twitter Follow + +
+ +
+ + Code License + + + Model License + +
+ +

+ Model Download | + Evaluation Results | + Model Architecture | + API Platform | + License | + Citation +

+ +

+ Paper Link👁️ +

+ +# DeepSeek-V2-Chat-0628 + +## 1. Introduction + +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. + +DeepSeek-V2-Chat-0628 has achieved remarkable performance on the LMSYS Chatbot Arena Leaderboard: + +Overall Ranking: #11, outperforming all other open-source models. + +

+ +

+ +Coding Arena Ranking: #3, showcasing exceptional capabilities in coding tasks. + +

+ +

+ +Hard Prompts Arena Ranking: #3, demonstrating strong performance on challenging prompts. + +

+ +

+ +## 2. Improvement + +Compared to the previous version DeepSeek-V2-Chat, the new version has made the following improvements: + +| **Benchmark** | **DeepSeek-V2-Chat** | **DeepSeek-V2-Chat-0628** | **Improvement** | +|:-----------:|:------------:|:---------------:|:-------------------------:| +| **HumanEval** | 81.1 | 84.8 | +3.7 | +| **MATH** | 53.9 | 71.0 | +17.1 | +| **BBH** | 79.7 | 83.4 | +3.7 | +| **IFEval** | 63.8 | 77.6 | +13.8 | +| **Arena-Hard** | 41.6 | 68.3 | +26.7 | +| **JSON Output (Internal)** | 78 | 85 | +7 | + +Furthermore, the instruction following capability in the "system" area has been optimized, significantly enhancing the user experience for immersive translation, RAG, and other tasks. + +## 3. How to run locally + +**To utilize DeepSeek-V2-Chat-0628 in BF16 format for inference, 80GB*8 GPUs are required.** +### Inference with Huggingface's Transformers +You can directly employ [Huggingface's Transformers](https://github.com/huggingface/transformers) for model inference. + +```python +import torch +from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig + +model_name = "deepseek-ai/DeepSeek-V2-Chat-0628" +tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True) +# `max_memory` should be set based on your devices +max_memory = {i: "75GB" for i in range(8)} +# `device_map` cannot be set to `auto` +model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True, device_map="sequential", torch_dtype=torch.bfloat16, max_memory=max_memory, attn_implementation="eager") +model.generation_config = GenerationConfig.from_pretrained(model_name) +model.generation_config.pad_token_id = model.generation_config.eos_token_id + +messages = [ + {"role": "user", "content": "Write a piece of quicksort code in C++"} +] +input_tensor = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt") +outputs = model.generate(input_tensor.to(model.device), max_new_tokens=100) + +result = tokenizer.decode(outputs[0][input_tensor.shape[1]:], skip_special_tokens=True) +print(result) +``` + +The complete chat template can be found within `tokenizer_config.json` located in the huggingface model repository. + +**Note: The chat template has been updated compared to the previous DeepSeek-V2-Chat version.** + +An example of chat template is as belows: + +```bash +<｜begin▁of▁sentence｜><｜User｜>{user_message_1}<｜Assistant｜>{assistant_message_1}<｜end▁of▁sentence｜><｜User｜>{user_message_2}<｜Assistant｜> +``` + +You can also add an optional system message: + +```bash +<｜begin▁of▁sentence｜>{system_message} + +<｜User｜>{user_message_1}<｜Assistant｜>{assistant_message_1}<｜end▁of▁sentence｜><｜User｜>{user_message_2}<｜Assistant｜> +``` + +### Inference with vLLM (recommended) +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. + +```python +from transformers import AutoTokenizer +from vllm import LLM, SamplingParams + +max_model_len, tp_size = 8192, 8 +model_name = "deepseek-ai/DeepSeek-V2-Chat-0628" +tokenizer = AutoTokenizer.from_pretrained(model_name) +llm = LLM(model=model_name, tensor_parallel_size=tp_size, max_model_len=max_model_len, trust_remote_code=True, enforce_eager=True) +sampling_params = SamplingParams(temperature=0.3, max_tokens=256, stop_token_ids=[tokenizer.eos_token_id]) + +messages_list = [ + [{"role": "user", "content": "Who are you?"}], + [{"role": "user", "content": "Translate the following content into Chinese directly: DeepSeek-V2 adopts innovative architectures to guarantee economical training and efficient inference."}], + [{"role": "user", "content": "Write a piece of quicksort code in C++."}], +] + +prompt_token_ids = [tokenizer.apply_chat_template(messages, add_generation_prompt=True) for messages in messages_list] + +outputs = llm.generate(prompt_token_ids=prompt_token_ids, sampling_params=sampling_params) + +generated_text = [output.outputs[0].text for output in outputs] +print(generated_text) +``` + +## 4. License +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. + +## 5. Citation +``` +@misc{deepseekv2, + title={DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model}, + author={DeepSeek-AI}, + year={2024}, + eprint={2405.04434}, + archivePrefix={arXiv}, + primaryClass={cs.CL} +} +``` + +## 6. Contact +If you have any questions, please raise an issue or contact us at [service@deepseek.com](service@deepseek.com). \ No newline at end of file