Hugging Face NLP Stack Pre-configured by Miri Infotech Inc. on Ubuntu

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About

Hugging Face NLP Stack Pre-Configured AMI is a ready-to-deploy, production-grade machine learning environment that eliminates setup headaches and lets you focus on building NLP applications.

Why Choose This AMI?

✅ Pre-Installed & Optimized – Comes with Hugging Face Transformers, PyTorch, TensorFlow, JupyterLab, and essential NLP libraries—no manual installation required.
✅ GPU-Accelerated – Optimized for AWS GPU instances (p3, p4, g4, g5) with CUDA and cuDNN pre-configured.
✅ Pre-Downloaded Models – Includes popular Hugging Face models (BERT, GPT, T5, RoBERTa) to save hours of download time.
✅ Secure & Scalable – IAM-based authentication, VPC-ready, and auto-scaling compatible.
✅ Beginner & Pro-Friendly – Works out of the box with example notebooks for quick onboarding.

Who Is This For?

🔹 AI Researchers – Quickly prototype transformer models without infrastructure hassles.
🔹 Data Scientists – Jump straight into fine-tuning and deploying NLP models.
🔹 Developers – Integrate Hugging Face into apps with minimal setup.
🔹 Educators – Teach NLP with a pre-configured environment.
🔹 Startups – Reduce DevOps overhead and accelerate AI product development.

You can subscribe to Mautic, an AWS Marketplace product and launch an instance from the product’s AMI using the Amazon EC2 launch wizard.

To launch an instance from the AWS Marketplace using the launch wizard

  • Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/
  • From the Amazon EC2 dashboard, choose Launch Instance. On the Choose an Amazon Machine Image (AMI) page, choose the AWS Marketplace category on the left. Find a suitable AMI by browsing the categories, or using the search functionality. Choose Select to choose your product.
  • A dialog displays an overview of the product you’ve selected. You can view the pricing information, as well as any other information that the vendor has provided. When you’re ready, choose Continue.
  • On the Choose an Instance Type page, select the hardware configuration and size of the instance to launch. When you’re done, choose Next: Configure Instance Details.
  • On the next pages of the wizard, you can configure your instance, add storage, and add tags. For more information about the different options you can configure, see Launching an Instance. Choose Next until you reach the Configure Security Group page.
  • The wizard creates a new security group according to the vendor’s specifications for the product. The security group may include rules that allow all IP addresses (0.0.0.0/0) access on SSH (port 22) on Linux or RDP (port 3389) on Windows. We recommend that you adjust these rules to allow only a specific address or range of addresses to access your instance over those ports
  • When you are ready, choose Review and Launch.
  • On the Review Instance Launch page, check the details of the AMI from which you’re about to launch the instance, as well as the other configuration details you set up in the wizard. When you’re ready, choose Launch to select or create a key pair, and launch your instance.
  • Depending on the product you’ve subscribed to, the instance may take a few minutes or more to launch. You are first subscribed to the product before your instance can launch. If there are any problems with your credit card details, you will be asked to update your account details. When the launch confirmation page displays.

Usage/Deployment Instructions

Step 1: SSH into your instance with username ubuntu and key pair to start the application

Username: ubuntu

ssh -i ssh_key.pem ubuntu@instance-IP

Goto below path:

cd /home/ubuntu

source hf_env/bin/activate

jupyter lab –allow-root

Connect via JupyterLab at http://<IP>:8888 (password = in /home/ubuntu/jupyter_password.txt).

 

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    Highlights

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      1-click AWS AMI with Hugging Face Transformers, Jupyter, and pre-loaded models (BERT/GPT/T5) - deploy NLP projects in minutes.

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      Pre-configured GPU-optimized NLP environment - just launch and start coding with Hugging Face.

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      Instant Hugging Face workspace: Jupyter + Transformers + popular models, ready on AWS in 5 minutes.

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      Skip the setup - AWS AMI with full Hugging Face stack and example notebooks pre-installed.

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      Production-ready NLP environment: Transformers, GPU support, and secure Jupyter access out-of-the-box.

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      From zero to NLP in 5 minutes - pre-configured AMI with all Hugging Face tools

    Application Installed

    • icon Linux