Janus-Pro is an advanced AI model built on the DeepSeek-LLM-7B-base, designed to handle both image and text tasks.
It uses a smart approach to separate image processing while keeping a unified system for understanding and generating content.
This helps it avoid conflicts between recognizing images and creating them.
With its SigLIP-L vision encoder, Janus-Pro processes images efficiently. It also comes with an optimized tokenizer to generate high-quality images.
Thanks to these features, it performs better than many existing AI models in various tests, making it one of the best in the field of AI-powered image and text processing.
If you want to install and run DeepSeek Janus Pro 7B on your local system, this detailed step-by-step guide will help you get started.
Installation Requirements for DeepSeek Janus-Pro 7B
Before you install DeepSeek Janus Pro 7B, ensure that your system meets the following hardware and software requirements.
These specifications are necessary to run the model smoothly without any performance issues.
Hardware Requirements
| GPU: | At least 1x RTX A6000 (or a similar high-performance GPU with ample VRAM) |
| Disk Space: | A minimum of 100 GB of free storage |
| RAM: | 64 GB (48 GB might work, but 64 GB is recommended for smoother execution) |
| CPU: | At least 64 cores (48 cores can work, but 64 cores offer better performance) |
Software Requirements
| Operating System: | Linux-based OS (Ubuntu recommended) |
| Python: | Version 3.11 or higher |
| Pip: | Latest version for dependency management |
| Git: | To clone the repository |
If you do not have a powerful local system, you can use cloud-based GPU servers like NodeShift, AWS, or Google Cloud.
Step-by-Step Guide to Install DeepSeek Janus Pro 7B
Step 1: Set Up a Virtual Machine (Optional, for Cloud Users)
Visit the NodeShift Platform and create an account. Once you’ve signed up, log into your account.
Follow the account setup process and provide the necessary details and information.
Create a GPU Node (Virtual Machine)
GPU Nodes are NodeShift’s GPU Virtual Machines, on-demand resources equipped with diverse GPUs ranging from H100s to A100s.
These GPU-powered VMs provide enhanced environmental control, allowing configuration adjustments for GPUs, CPUs, RAM, and Storage based on specific requirements.
Navigate to the menu on the left side.
Select the GPU Nodes option, create a GPU Node in the Dashboard, click the Create GPU Node button, and create your first Virtual Machine deployment.
Select a Model, Region, and Storage
In the “GPU Nodes” tab, select a GPU Model and Storage according to your needs and the geographical region where you want to launch your model.
We will use 1x RTX A6000 GPU for this tutorial to achieve the fastest performance.
However, you can choose a more affordable GPU with less VRAM if that better suits your requirements.
Select Authentication Method
There are two authentication methods available: Password and SSH Key.
SSH keys are a more secure option. To create them, please refer to our official documentation.
Choose an Image
Next, you will need to choose an image for your Virtual Machine.
We will deploy DeepSeek Janus Pro 7B on an NVIDIA Cuda Virtual Machine.
This proprietary, closed-source parallel computing platform will allow you to install DeepSeek Janus Pro 7B on your GPU Node.
After choosing the image, click the ‘Create’ button, and your Virtual Machine will be deployed.
Virtual Machine Successfully Deployed
You will get visual confirmation that your node is up and running.
Connect to GPUs using SSH
NodeShift GPUs can be connected to and controlled through a terminal using the SSH key provided during GPU creation.
Once your GPU Node deployment is successfully created and has reached the ‘RUNNING’ status, you can navigate to the page of your GPU Deployment Instance.
Then, click the ‘Connect’ button in the top right corner.
Now open your terminal and paste the proxy SSH IP or direct SSH IP.
Step 2: Verify GPU Availability
Before proceeding with installation, check if your GPU is detected by running the following command:
nvidia-smi
If your GPU is listed, you are ready to proceed.
Step 3: Check the Available Python version and Install the new version
Run the following commands to check the available Python version.
If you check the version of the python, system has Python 3.8.1 available by default.
To install a higher version of Python, you’ll need to use the deadsnakes PPA.
Run the following commands to add the deadsnakes PPA:
sudo apt update
sudo apt install -y software-properties-common
sudo add-apt-repository -y ppa:deadsnakes/ppa
sudo apt update
Now, run the following command to install Python 3.11 or another desired version:
sudo apt install -y python3.11 python3.11-distutils python3.11-venv
Step 4: Update the Default Python3 Version
Now, run the following command to link the new Python version as the default python3:
sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.8 1
sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.11 2
sudo update-alternatives --config python3Then, run the following command to verify that the new Python version is active:
python3 --version
Step 5: Install and Update Pip
Pip is required for installing dependencies. Install or update pip using:
python3 -m ensurepip --upgrade
python3 -m pip install --upgrade pipThen, run the following command to check the version of pip:
pip --version
Step 6: Clone the DeepSeek Janus Repository
Now, download the DeepSeek Janus Pro 7B repository from GitHub:
git clone https://github.com/deepseek-ai/Janus.git
cd Janus
Step 7: Install Required Dependencies
Install the necessary libraries using:
pip install -e .
For Gradio support, which enables a web-based user interface, install:
pip install -e .[gradio]
Step 8: Start the DeepSeek Janus Pro 7B Server
Once everything is set up, start the AI model’s server using:
python3 demo/app_januspro.py
Accessing the application at:
Running on local URL: http://127.0.0.1:7860
Running on public URL: https://0fac078df655921b11.gradio.live
Step 9: Multimodal Understanding
Step 10: Text-to-Image Generation
Conclusion
Installing DeepSeek Janus Pro 7B locally may seem complex, but by following these steps, you can set it up with ease.
Whether you’re running it on a local machine or a cloud-based GPU server, this AI model provides powerful multimodal capabilities for various applications.
With the right hardware and setup, you can explore its full potential in AI-driven tasks.
If you run into issues, check the official resources:
- Hugging Face: DeepSeek Janus Pro 7B
- GitHub: DeepSeek Janus Repository
