AI/ML
Deploy StarCoder on Your Local Machine with Docker & Hugging Face
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Free Installation Guide - Step by Step Instructions Inside!
Introduction
StarCoder is a high performance AI model optimized for code generation. To run it on a local server, we will use Docker to ensure a stable and isolated environment and Hugging Face Transformers to download and execute the model.
System Requirements
Before starting, ensure your local server meets the following:
- Ubuntu 20.04+ or Debian-based OS
- Docker installed (if not, install it using the steps below)
- At least 16GB RAM for smooth model execution
Step 1: Install Docker (If Not Already Installed)
To set up Docker on your local server run
sudo apt update && sudo apt upgrade -ysudo apt install docker.io -ysudo systemctl start dockersudo systemctl enable dockerVerify the installation:
docker --version Step 2: Set Up a Docker Container for StarCoder
Create a container with Python and necessary libraries:
docker run -it --name starcoder-container --rm -p 8000:8000 python:3.9 bashInside the container, install dependencies:
pip install torch transformers flaskStep 3: Download StarCoder from Hugging Face
Now, download the StarCoder model:
from transformers import AutoModelForCausalLM, AutoTokenizertokenizer = AutoTokenizer.from_pretrained("bigcode/starcoder")model = AutoModelForCausalLM.from_pretrained("bigcode/starcoder")
This fetches the model and tokenizer from Hugging Face.
Step 4: Running the Model as a Local API
Create a simple Flask server to expose StarCoder’s API:
from flask import Flask, request, jsonify
def generate_code(prompt): inputs = tokenizer(prompt, return_tensors="pt") output = model.generate(**inputs, max_length=200) return tokenizer.decode(output[0])app = Flask(__name__)@app.route("/generate", methods=["POST"])def generate(): data = request.json response = generate_code(data["prompt"]) return jsonify({"response": response})if __name__ == "__main__": app.run(host="0.0.0.0", port=8000)
Save this as server.py inside the container.
Step 5: Running the API Server
Inside the Docker container, start the server:
python server.py
Your StarCoder API is now live at:
http://localhost:8000/generate
You can send a POST request with a prompt:
{ "prompt": "def fibonacci(n):"}
Summary: Can You Run StarCoder?
With this setup, you have StarCoder running in a Docker container on a local server, accessible via an API. This approach ensures flexibility and easy deployment for local AI based coding assistance.
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AI/ML