Name: DeepSeek Coder 33B
Author: DeepSeek

Overview

DeepSeek Coder 33B is a specialized large language model optimized for end-to-end software development. Unlike general-purpose LLMs, it is trained on a massive corpus of code, making it highly proficient in complex logic synthesis, bug detection, and multi-language translation. For developers, this means higher accuracy in generating boilerplate-free code and a deeper understanding of architectural patterns across diverse frameworks. It serves as a powerful alternative to larger proprietary models, offering a strong balance between inference latency and reasoning capabilities. Whether integrated into a custom IDE plugin or used for automated code reviews, the model handles long-context windows effectively, allowing it to maintain consistency across larger files and modules.

Highlights

High-precision code generation across multiple programming languages
Strong logical reasoning for complex debugging and refactoring
Optimized 33B parameter size for efficient local deployment
Deep understanding of software architecture and design patterns
Seamless integration into developer workflows and IDEs

Usage

Install

# Install Hugging Face transformers
pip install transformers torch

SDK Usage

# Load model with transformers
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("deepseek-ai/deepseek-coder-33b")
tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-33b")

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance：Before downloading, install huggingface_hub with:

Guidance

pip install -U huggingface_hub

CLI Download

Download the full repository

huggingface-cli download deepseek-ai/deepseek-coder-33b

Download a single file to a local folder (e.g. config.json into ./dir)

huggingface-cli download deepseek-ai/deepseek-coder-33b config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('deepseek-ai/deepseek-coder-33b')

Git Download

Make sure git-lfs is installed first

Git Download

git lfs install
git clone https://huggingface.co/deepseek-ai/deepseek-coder-33b

To skip LFS large-file downloads, use:

Skip LFS

GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/deepseek-ai/deepseek-coder-33b

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

pip install -U transformers torch

Load the model and run inference

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('deepseek-ai/deepseek-coder-33b')
tokenizer = AutoTokenizer.from_pretrained('deepseek-ai/deepseek-coder-33b')

Model Download

We recommend downloading the model via the ModelScope CLI or SDK.

Guidance：Before downloading, install ModelScope with:

Guidance

pip install modelscope

CLI Download

Download the full repository

modelscope download --model deepseek-ai/DeepSeek-V3

Download a single file to a local folder (e.g. README.md into ./dir)

modelscope download --model deepseek-ai/DeepSeek-V3 README.md --local_dir ./dir

See the docs for more CLI options

SDK Download

# 模型下载
from modelscope import snapshot_download
model_dir = snapshot_download('deepseek-ai/DeepSeek-V3')

Git Download

Make sure git-lfs is installed first

Git Download

git lfs install
git clone https://www.modelscope.cn/deepseek-ai/DeepSeek-V3.git

To skip LFS large-file downloads, use:

Skip LFS

GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/deepseek-ai/DeepSeek-V3.git

ModelScope 模型页直接下载模型文件；无需将模型文件放在本站服务器。

Notebook Quickstart

Install the ModelScope library

pip install "modelscope[audio,cv,nlp,multi-modal,science]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html

Load the model and run inference

from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks

p = pipeline('text-generation', 'deepseek-ai/DeepSeek-V3')