Guanaco

Maintained By
JosephusCheung

Guanaco

PropertyValue
Base ModelLLaMA 7B
LicenseGPL-3.0
Supported LanguagesEnglish, Chinese, Japanese, German
AuthorJosephusCheung

What is Guanaco?

Guanaco is an advanced instruction-following language model that builds upon Meta's LLaMA 7B architecture. It extends the original Alpaca dataset from 52K to over 534K entries, incorporating multiple languages and specialized linguistic tasks. The model is particularly notable for its enhanced multilingual capabilities and sophisticated role-playing support.

Implementation Details

The model implements a structured conversation format similar to ChatGPT, with clear delineation between instruction, input, and response sections. It utilizes fp16 inference for optimal performance and includes specialized features for handling context and multiple conversation turns.

  • Advanced prompt role support with structured conversation format
  • Sophisticated role-playing capabilities across multiple languages
  • Improved context handling and response continuation
  • Specialized rejection handling with reserved keywords (NO IDEA, FORBIDDEN, SFW)

Core Capabilities

  • Multilingual support for EN, ZH, JA, and DE
  • Character-based role-playing similar to Character.AI
  • Context-aware conversations with history tracking
  • Knowledge-based responses with source verification support
  • Explicit content filtering and ethical consideration handling

Frequently Asked Questions

Q: What makes this model unique?

Guanaco stands out for its extensive multilingual capabilities and sophisticated role-playing support, built on a significantly expanded dataset compared to the original Alpaca model. It includes specialized features for handling different types of conversations and content filtering.

Q: What are the recommended use cases?

The model is well-suited for multilingual conversations, role-playing scenarios, and general instruction-following tasks. However, for knowledge-based queries, it's recommended to provide verifiable sources in the System Prompt to ensure accuracy.

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