--- license: other license_name: deepseek license_link: https://github.com/deepseek-ai/DeepSeek-MoE/blob/main/LICENSE-MODEL ---

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### 1. Introduction to DeepSeekMoE See the [Introduction](https://github.com/deepseek-ai/DeepSeek-MoE/blob/main) for more details. ### 2. How to Use Here give some examples of how to use our model. #### Text Completion ```python import torch from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig model_name = "deepseek-ai/deepseek-moe-16b-base" 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 text = "An attention function can be described as mapping a query and a set of key-value pairs to an output, where the query, keys, values, and output are all vectors. The output is" inputs = tokenizer(text, return_tensors="pt") outputs = model.generate(**inputs.to(model.device), max_new_tokens=100) result = tokenizer.decode(outputs[0], skip_special_tokens=True) print(result) ``` ### 3. License This code repository is licensed under the MIT License. The use of DeepSeekMoE models is subject to the Model License. DeepSeekMoE supports commercial use. See the [LICENSE-MODEL](https://github.com/deepseek-ai/DeepSeek-MoE/blob/main/LICENSE-MODEL) for more details. ### 4. Contact If you have any questions, please raise an issue or contact us at [service@deepseek.com](mailto:service@deepseek.com).