--- license: other license_name: deepseek license_link: LICENSE model-index: - name: deepseek-llm-67b-chat results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 67.75 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=deepseek-ai/deepseek-llm-67b-chat name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 86.82 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=deepseek-ai/deepseek-llm-67b-chat name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 72.42 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=deepseek-ai/deepseek-llm-67b-chat name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 55.85 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=deepseek-ai/deepseek-llm-67b-chat name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 84.21 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=deepseek-ai/deepseek-llm-67b-chat name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 63.68 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=deepseek-ai/deepseek-llm-67b-chat name: Open LLM Leaderboard ---

DeepSeek Chat

[šŸ Homepage] | [šŸ¤– Chat with DeepSeek LLM] | [Discord] | [Wechat(å¾®äæ”)]

### 1. Introduction of Deepseek LLM Introducing DeepSeek LLM, an advanced language model comprising 67 billion parameters. It has been trained from scratch on a vast dataset of 2 trillion tokens in both English and Chinese. In order to foster research, we have made DeepSeek LLM 7B/67B Base and DeepSeek LLM 7B/67B Chat open source for the research community. ### 2. Model Summary `deepseek-llm-67b-chat` is a 67B parameter model initialized from `deepseek-llm-67b-base` and fine-tuned on extra instruction data. - **Home Page:** [DeepSeek](https://deepseek.com/) - **Repository:** [deepseek-ai/deepseek-LLM](https://github.com/deepseek-ai/deepseek-LLM) - **Chat With DeepSeek LLM:** [DeepSeek-LLM](https://chat.deepseek.com/) ### 3. How to Use Here give some examples of how to use our model. #### Chat Completion ```python import torch from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig model_name = "deepseek-ai/deepseek-llm-67b-chat" tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto") model.generation_config = GenerationConfig.from_pretrained(model_name) model.generation_config.pad_token_id = model.generation_config.eos_token_id messages = [ {"role": "user", "content": "Who are you?"} ] 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) ``` 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. ``` User: {messages[0]['content']} Assistant: {messages[1]['content']}<ļ½œendā–ofā–sentenceļ½œ>User: {messages[2]['content']} Assistant: ``` **Note:** By default (`add_special_tokens=True`), our tokenizer automatically adds a `bos_token` (`<ļ½œbeginā–ofā–sentenceļ½œ>`) 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. ### 4. License This code repository is licensed under the MIT License. The use of DeepSeek LLM models is subject to the Model License. DeepSeek LLM supports commercial use. See the [LICENSE-MODEL](https://github.com/deepseek-ai/deepseek-LLM/blob/main/LICENSE-MODEL) for more details. ### 5. Contact If you have any questions, please raise an issue or contact us at [service@deepseek.com](mailto:service@deepseek.com). # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_deepseek-ai__deepseek-llm-67b-chat) | Metric |Value| |---------------------------------|----:| |Avg. |71.79| |AI2 Reasoning Challenge (25-Shot)|67.75| |HellaSwag (10-Shot) |86.82| |MMLU (5-Shot) |72.42| |TruthfulQA (0-shot) |55.85| |Winogrande (5-shot) |84.21| |GSM8k (5-shot) |63.68|