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deepseek-ai/deepseek-v3

104k stars Python View on GitHubprofiled 11d ago
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01 · Repo overview

How deepseek-v3 is put together

This repository is the official release of DeepSeek-V3, a 671B-parameter Mixture-of-Experts language model (37B activated per token). It is primarily a model-weights and documentation distribution: the README presents the architecture (MLA attention, DeepSeekMoE, auxiliary-loss-free load balancing, multi-token prediction), benchmark results, and download links to Hugging Face. The only executable code is a minimal Python inference pipeline under inference/, which loads safetensors checkpoints and runs autoregressive generation with PyTorch/Triton kernels, including FP8-to-BF16 weight conversion utilities. There is no web service, datastore, or deployment infrastructure in the repo; data flow is checkpoint files -> weight conversion/loading -> forward pass -> generated text.

Languages

Python

Frameworks

PyTorchTransformersTriton

Major components

inference/model

Implements the DeepSeek-V3 transformer architecture (MoE layers, MLA attention) for local inference.

inference/generate

Entry-point script that drives autoregressive text generation from loaded model weights.

inference/kernel

Custom Triton/CUDA-style kernels used by the inference path.

inference/fp8_cast_bf16

Utility that casts FP8 quantized checkpoint weights to BF16.

inference/convert

Checkpoint conversion tooling for preparing model weights for inference.

inference/configs

JSON model configuration files for 16B, 236B, 671B variants and v3.1.

documentation

README.md and README_WEIGHTS.md describing the model, benchmarks, weight layout including MTP modules, and licensing.

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03 · Security check

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