Autocomplete Role in Continue Models

Learn how the autocomplete role works in Continue, which models to use, and how to customize prompt templates for inline code suggestions.

An “autocomplete model” is an LLM that is trained on a special format called fill-in-the-middle (FIM). This format is designed to be given the prefix and suffix of a code file and predict what goes between. This task is very specific, which on one hand means that the models can be smaller (even a 3B parameter model can perform well). On the other hand, this means that Chat models, though larger, will often perform poorly even with extensive prompting.

In Continue, autocomplete models are used to display inline Autocomplete suggestions as you type. Autocomplete models are designated by adding the autocomplete to the model’s roles in config.yaml.

Recommended Autocomplete models

Model role	Best open models	Best closed models	Notes
Autocomplete	QwenCoder2.5 (1.5B) QwenCoder2.5 (7B)	Codestral Mercury Coder	Closed models are slightly better than open models

Visit the Autocomplete Deep Dive for detailed setup instructions and configuration options.

Prompt templating

You can customize the prompt template used when autocomplete happens by setting the promptTemplates.autocomplete property in your model configuration. Continue uses Handlebars syntax for templating.

Available variables for the apply template:

• {{{prefix}}} - the code before your cursor
• {{{suffix}}} - the code after your cursor
• {{{filename}}} - the name of the file your cursor currently is
• {{{reponame}}} - the name of the folder where the codebase is
• {{{language}}} - the name of the programming language in full (ex. Typescript)

Example:

models:
  - name: My Custom Autocomplete Template
    provider: ollama
    model: qwen2.5-coder:1.5b
    promptTemplates:
      autocomplete: |
        `
        globalThis.importantFunc = importantFunc
        <|fim_prefix|>{{{prefix}}}<|fim_suffix|>{{{suffix}}}<|fim_middle|>
        `