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The DeepSeek-LLM repository hosts the code, model files, evaluations, and documentation for DeepSeek’s LLM series (notably the 67B Chat variant). Its tagline is “Let there be answers.” The repo includes an “evaluation” folder (with results like math benchmark scores) and code artifacts (e.g. pre-commit config) that support model development and deployment. According to the evaluation files, DeepSeek LLM 67B Chat achieves strong performance on math benchmarks under both chain-of-thought (CoT) and tool-assisted reasoning modes. The model is trained from scratch, reportedly on a vast multilingual + code + reasoning dataset, and competes with other open or open-weight models. The architecture mirrors established decoder-only transformer families: pre-norm structure, rotational embeddings (RoPE), grouped query attention (GQA), and mixing in languages and tasks. It supports both “Base” (foundation model) and “Chat” (instruction / conversation tuned) variants.
Features
- DeepSeek LLM 67B Chat with evaluated benchmark results (math, reasoning, etc)
- Support both chain-of-thought and tool-integrated reasoning modes
- Common transformer architecture components: pre-norm, RoPE embeddings, GQA
- Model variants: Base version and Chat / instruction-tuned version
- Evaluation metrics, benchmark comparisons (GSM8K, MATH, MGSM-zh, etc) included
- Configuration, code, and infrastructure files (e.g. .pre-commit-config.yaml) to support development and deployment
Project Samples
