NanoCoder is a Fill-in-the-Middle (FIM) language model specifically designed for React frontend development and coding assistance. It helps users with intelligent code autocompletion and context-aware generation. The model was fine-tuned using Unsloth on the Qwen 3 0.6B base model, leveraging a high-quality FIM dataset curated from GitHub repositories to enhance coding capabilities and developer productivity.
🧠 Datasets
We trained NanoCoder using a high-quality Fill-in-the-Middle (FIM) dataset curated from GitHub repositories:
srisree/nextjs_typescript_fim_dataset on Hugging Face.
This dataset focuses on React/Next.js and TypeScript projects, providing rich, real-world coding examples that help the model understand frontend architecture, component composition, and React ecosystem patterns.
By leveraging this dataset, NanoCoder learns to:
- Predict and fill missing code intelligently using FIM objectives.
- Understand React component structures and TypeScript typing patterns.
- Generate clean, production-grade frontend code snippets.
⚙️ FIM Training Colab Script
We’re preparing an interactive Google Colab notebook for reproducing the Fill-in-the-Middle (FIM) fine-tuning process used to train NanoCoder with Unsloth on the Qwen 3 0.6B base model.
The Colab script will include:
- ✅ Environment setup with Unsloth and Qwen 3 0.6B
- ✅ Loading and preprocessing the Next.js TypeScript FIM Dataset
- ✅ Training configuration (LoRA, batch size, sequence length, etc.)
- ✅ Evaluation and inference examples
🚀 Coming soon... Stay tuned for the full release!
⚙️ Setup and Run NanoCoder Locally with Ollama in VS Code
Step-by-step guide to install, configure, and use NanoCoder for intelligent React frontend code completion with the Continue VS Code extension.
🧠 Prerequisites
Before getting started, ensure you have the following installed:
- VS Code
- Ollama (latest version)
- Continue extension
- A system with at least 8GB RAM (recommended for 0.6B models)
🧩 Step 1: Install Ollama
If you haven’t already, download and install Ollama:
- macOS / Linux / Windows: https://ollama.ai/download
Once installed, open your terminal and verify the installation.
💾 Step 2: Pull NanoCoder Model
ollama pull srisree/nanocoder
⚡ Step 3: Run NanoCoder with Ollama
Once downloaded, you can test NanoCoder directly in the terminal:
ollama run nanocoder
Read more Continue Docs