continuedev/instinct
Instinct is a 7.6 billion parameter open Next Edit model developed by Continue, fine-tuned from Qwen2.5-Coder-7B. This model is specifically designed and optimized for predicting real-world code edits, aiming to enhance developer workflow and maintain flow state. With a substantial context length of 131072 tokens, Instinct excels at intelligently suggesting the next code modifications.
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Instinct: A Next-Generation Code Editing Model
Instinct is a 7.6 billion parameter open-source model developed by Continue, specifically engineered for advanced code editing. Fine-tuned from Qwen2.5-Coder-7B, Instinct leverages a unique dataset of real-world code edits to intelligently predict and suggest the next logical code modifications, aiming to keep developers in a state of flow.
Key Capabilities
- Intelligent Code Prediction: Predicts subsequent code edits based on real-world developer patterns.
- Flow State Enhancement: Designed to integrate seamlessly into development workflows, minimizing interruptions.
- Robust Fine-tuning: Built upon Qwen2.5-Coder-7B and extensively fine-tuned on a proprietary dataset of code edits.
- High Context Length: Supports a substantial context window of 131072 tokens, allowing for comprehensive understanding of larger codebases.
Deployment Options
Instinct is available for various deployment methods, including:
- Ollama: A Q4_K_M GGUF quantization is provided for efficient local inference.
- SGLang & vLLM: Supports serving via SGLang and vLLM for integration with Continue's self-hosting options.
For more in-depth information, refer to the Continue blog post on Instinct.