Gurubot/cage-600m

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:0.8BQuant:BF16Ctx Length:32kPublished:Apr 1, 2026Architecture:Transformer Warm

Gurubot/cage-600m is a 0.8 billion parameter model developed by Gurubot, specifically designed as a Constrained Answer Generation Engine (CAGE). This model eliminates hallucination by restricting its output to a predetermined list of approved placeholder tokens, which are then substituted with full, pre-approved responses. It excels in applications requiring highly accurate, consistent, and non-hallucinatory responses, such as customer support chatbots, by ensuring all outputs are curated and controlled.

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Overview

Gurubot/cage-600m is a specialized 0.8 billion parameter model designed as a Constrained Answer Generation Engine (CAGE). Its core innovation is to eliminate hallucination by preventing the model from generating free-form text. Instead, it outputs specific placeholder tokens (e.g., {answerResetPassword}), which are then replaced by pre-approved, human-written responses by your application code. This approach ensures that all chatbot outputs are accurate, consistent, and cannot invent non-existent information or policies.

Key Capabilities

  • Guaranteed No Hallucination: The model can only select from a predefined set of responses, making it impossible to generate incorrect or fabricated information.
  • Consistent Response Style: Ensures uniform tone and content as responses are written and approved by your team.
  • Easy Localization: Supports multiple language mapping files for placeholders, simplifying multilingual deployments.
  • Prompt Injection Resilient: The model's output remains constrained to placeholders, mitigating risks from malicious prompt injections.
  • Resource Efficient: Its small size (0.8B parameters) allows for deployment on systems with limited VRAM or no GPU, while still performing reliably for its specialized task.
  • Tool Calling Integration: Placeholder outputs can serve as simple triggers for tool calls (e.g., {urlBrightBankLogin} to open a login page).

Good For

  • Customer Support Chatbots: Ideal for scenarios where accuracy and adherence to company policies are critical, preventing legal liabilities from hallucinated information.
  • FAQ Systems: Ensures precise answers to frequently asked questions.
  • Interactive Dialog Trees: Can be integrated with dynamic response tables to create structured conversational flows.
  • Applications Requiring High Output Control: Any use case where the exact wording and factual correctness of AI-generated responses are paramount.