QwQ-35B-Eureka-Cubed-gguf

Maintained By
DavidAU

QwQ-35B-Eureka-Cubed-gguf

PropertyValue
Base ModelQwQ-32B
Parameter Count~35B
Required TemplateChatML
AuthorDavidAU
Context Length4K-8K+ recommended

What is QwQ-35B-Eureka-Cubed-gguf?

QwQ-35B-Eureka-Cubed is an enhanced version of the QwQ-32B model, incorporating additional capabilities from TinyR1-32b-preview and DeepSeek-R1-Distill-Qwen-32B. The model uses the "Cubed" method, which adds four additional layers and approximately 2 billion parameters to enhance reasoning and output generation capabilities.

Implementation Details

The model requires the ChatML template without a system prompt, though an optional system prompt is provided for unrestricted usage. Optimal parameters include temperature range of 0.4 to 0.8, repetition penalty of 1.02 to 1.1, TopK 40, topP 0.95, and minP 0.05. The context window is recommended to be at least 4K, with 8K+ being optimal.

  • Enhanced reasoning capabilities with decreased problem-solving time
  • Improved output quality and creativity for both scientific and creative content
  • Multiple conclusion layers from multiple models in series
  • Ability to exceed context limits without breaking

Core Capabilities

  • Superior instruction following and comprehension
  • Enhanced reasoning and thinking abilities
  • Detailed and insightful output generation
  • Versatile use across multiple domains
  • Ability to handle long-form content (up to 12k output with 4k context)

Frequently Asked Questions

Q: What makes this model unique?

The model combines the exceptional reasoning capabilities of QwQ-32B with additional features from TinyR1 and DeepSeek models, creating a more powerful system for both reasoning and output generation. The "Cubed" method adds multiple conclusion layers, enhancing overall performance.

Q: What are the recommended use cases?

The model is designed for all use cases, including creative writing, scientific analysis, brainstorming, and general instruction following. It excels in both reasoning tasks and detailed output generation, making it suitable for complex problem-solving and creative endeavors.

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