AI/ML
How to Install Sarvam AI Bulbul v2 on AWS EC2 via Hugging Face - Step by Step Guide
Introduction
Automate Your Business with AI & Say Goodbye to Manual Work!
Are you tired of repetitive tasks eating up your time? What{{description}}: What if you could deploy your own powerful Open Source AI model like Sarvam AI Bulbul v2 in minutes and let it handle the heavy lifting? In this step by step Center of Excellence guide, we’ll walk you through installing Bulbul v2 on AWS EC2 via Hugging Face so you can focus on scaling your business while AI does the work!
Why Choose Sarvam AI Bulbul v2?
✅ Open Source and Easy to customize
✅ Cutting edge voice & text AI
✅ Easy AWS deployment
✅ Cost efficient & scalable
✅ Deploy on your owned server
✅ Perfect for automating customer support, content creation and more!
Let’s dive in!
Prerequisites: What You’ll Need
Before we begin, make sure you have
- An AWS account (Free tier works!)
- Basic familiarity with AWS EC2 & SSH
- Hugging Face account (for model access)
- A dash of enthusiasm for AI automation
Step by Step: Deploying Sarvam AI Bulbul v2 on AWS EC2
Step 1: Launch an AWS EC2 Instance
- Log in to your AWS Console.
- Navigate to EC2 Dashboard > Launch Instance.
- Choose an Ubuntu 22.04 LTS AMI (free tier eligible).
- Select t2.medium (or higher for better performance).
- Configure storage (30GB recommended).
- Enable HTTP/HTTPS traffic in security groups.
- Launch & download your key pair (.pem file).
Pro Tip: Use a larger instance (e.g., g4dn.xlarge) if you need GPU acceleration!
Step 2: Connect to Your EC2 Instance via SSH
Open Terminal (Mac/Linux) or PowerShell (Windows).
Run:
chmod 400 your-key.pemssh -i "your-key.pem" ubuntu@your-ec2-public-ipYou’re in! Time to set up the environment.
Step 3: Install Dependencies
sudo apt update && sudo apt upgrade -ysudo apt install -y python3-pip gitpip3 install torch transformers huggingface-hubWhy this matters? These packages ensure Bulbul v2 runs smoothly with Hugging Face integration.
Step 4: Download Sarvam AI Bulbul v2 from Hugging Face
Get your Hugging Face API token from huggingface.co/settings/tokens.
Run:
huggingface-cli login(Enter your API token when prompted.)
Now, download the model:
from transformers import AutoModelForCausalLM, AutoTokenizermodel = AutoModelForCausalLM.from_pretrained("sarvamai/Bulbul-v2")tokenizer = AutoTokenizer.from_pretrained("sarvamai/Bulbul-v2")Boom! You’ve got Bulbul v2 ready to roll.
Step 5: Run the Model & Test It
Create a Python script (test_bulbul.py) and run:from transformers import pipelinepipe = pipeline("text-generation", model="sarvamai/Bulbul-v2")output = pipe("Explain quantum computing simply")print(output)Try it out! Ask Bulbul anything - it’s like having an AI assistant on standby.
Final Thoughts: Your AI Powered Future Starts Now!
Congratulations! 🥳 You’ve just deployed Sarvam AI Bulbul v2 on AWS EC2- no more tedious manual tasks!
Use Cases to Explore:
✔ Automated customer support
✔ AI content generation
✔ Voice enabled applications
📢 Now It’s Your Turn!
👉 Have questions? Drop them in the comments! We will reply back with your answers.
👉 Want more AI automation guides? Refer to our 50Days50AutomationChallenges Daily Articles
👉 Want more AI Models Installation guides? Refer to our Center of Excellence AI Arcticles
🚀 The future is automated - don’t get left behind!
Quick Checklist Before You Go
✅ Launched AWS EC2 instance
✅ Installed Python & dependencies
✅ Logged into Hugging Face
✅ Downloaded Bulbul v2
✅ Tested the model
Ready to transform your business with our technology solutions? Contact Us today to Leverage Our AI/ML Expertise.
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