RUNLOCALAIv38
->Will it run?Best GPUCompareTroubleshootStartLearnPulseModelsHardwareToolsBench
Run check
RUNLOCALAI

Independently operated catalog for local-AI hardware and software. Hand-written verdicts. Source-cited claims. Reproducible commands when we have them.

OP·Eruo Fredoline
DIR
  • Models
  • Hardware
  • Tools
  • Benchmarks
TOOLS
  • Will it run?
  • Compare hardware
  • Cost vs cloud
  • Choose my GPU
  • Prompting kits
  • Quick answers
REF
  • All buyer guides
  • Learn local AI
  • Methodology
  • Glossary
  • Errors KB
  • Trust
EDITOR
  • About
  • Author
  • How we make money
  • Editorial policy
  • Contact
LEGAL
  • Privacy
  • Terms
  • Sitemap
MAIL · MONTHLY DIGEST
Get monthly local AI changes
Monthly recap. No spam.
DISCLOSURE

Some links on this site are affiliate links (Amazon Associates and other first-class retailers). When you buy through them, we earn a small commission at no extra cost to you. Affiliate links do not influence our verdicts — there are cards we rate highly that we don't have affiliate relationships with, and cards that sell well that we refuse to recommend. Read more →

© 2026 runlocalai.coIndependently operated
RUNLOCALAI · v38
  1. >
  2. Home
  3. /Learn
  4. /Courses
  5. /Ollama — Installation to Mastery
  6. /Ch. 16
Ollama — Installation to Mastery

16. Continue.dev Integration

Chapter 16 of 20 · 15 min
KEY INSIGHT

Continue uses Ollama for both chat and autocomplete, but autocomplete requires fast response times. Use smaller models for autocomplete and reserve larger models for complex code questions in chat.

Continue.dev is a VS Code extension that uses Ollama for code completion and chat. It integrates directly into the IDE, providing context-aware assistance while you write code.

Installation

  1. Install VS Code
  2. Open Extensions (Ctrl+Shift+X)
  3. Search for "Continue" and install the "Continue" extension

Configuration

After installation, open the Continue settings (click the Continue icon in the sidebar or press Ctrl+Shift+=). Configure the Ollama connection:

{
  "models": [
    {
      "title": "Codellama",
      "provider": "ollama",
      "model": "codellama:7b",
      "api_base": "http://localhost:11434"
    }
  ],
  "tabAutocompleteModel": {
    "title": "Codellama",
    "provider": "ollama",
    "model": "codellama:7b",
    "api_base": "http://localhost:11434"
  }
}

The models array configures chat models, while tabAutocompleteModel sets the model used for inline code completion.

Features

  • Inline completion - Autocomplete suggestions as you type, powered by the tabAutocompleteModel.
  • Chat panel - Ask questions about your codebase in the sidebar.
  • Context retrieval - Continue automatically includes relevant file contents in prompts.

Model Selection

Continue works best with code-focused models:

  • codellama:7b - General code completion and explanation
  • codellama:13b - More capable, requires more VRAM
  • deepseek-coder:6.7b - Specialized for code generation

For autocomplete specifically, smaller models (7B parameters) respond faster and work well for single-line completions.

Troubleshooting

No completions appearing:

  1. Verify Ollama is running: curl http://localhost:11434
  2. Check the api_base in Continue settings matches your Ollama URL
  3. Try a different model-some models are not well-tuned for code completion

Slow responses:

  1. Reduce the tabAutocompleteModel size (try codellama:3b instead of 7b)
  2. Limit context by adjusting Continue's retrieval settings
  3. Ensure GPU acceleration is working (see Chapter 8)

Model not found:

  1. Pull the model: ollama pull codellama:7b
  2. Check the model name in Continue settings matches exactly (including version tag)
EXERCISE

Install Continue, configure it with codellama:7b, and verify inline completions work in a Python file. If completion is slow, switch to codellama:3b and compare response times.

← Chapter 15
Open WebUI Integration
Chapter 17 →
GPU Not Detected