Base Models: The Foundation of Your Vibe
Definition: A pre-trained model serving as a starting point for fine-tuning to address specific tasks or applications.
Base Model vs. Chat Model
- Base Model: Predicts the next word. (e.g.,
Llama-3-70b-base). If you type “What is the capital of France?”, it might complete it with “and its population?” because it thinks it’s writing a geography quiz. - Instruct/Chat Model: Fine-tuned to answer questions. (e.g.,
GPT-4,Claude-3-Opus).
Why Vibe Coders Need Base Models
Most of the time, you use Chat models. But for Code Autocomplete (like Ghostwriter or Copilot FIM), Base Models are often better.
- Fill-In-The-Middle (FIM): You have the top of the file and the bottom. You need the middle. A Base Model trained on code is excellent at “bridging the gap” because it understands the statistical flow of code syntax better than a Chat model that tries to “talk” to you.
Choosing Your Base
If you run local AI (using Ollama):
- CodeLlama: Good for strict syntax.
- DeepSeek Coder: Currently the “Vibe King” of open weights coding models.
- Mistral: Good all-rounder.
Expert Takeaway
Know your tools. Use Chat Models to plan and debug. Use Base Models (via autocomplete plugins) to type. They are different vibes for different modes of work.