Qwen3.5-27B-Engineer-Deckard-Claude
128
license:apache-2.0
by
nightmedia
Image Model
OTHER
27B params
New
128 downloads
Early-stage
Edge AI:
Mobile
Laptop
Server
61GB+ RAM
Mobile
Laptop
Server
Quick Summary
AI model with specialized capabilities.
Device Compatibility
Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
26GB+ RAM
Training Data Analysis
🟡 Average (4.3/10)
Researched training datasets used by Qwen3.5-27B-Engineer-Deckard-Claude with quality assessment
Specialized For
general
science
multilingual
reasoning
Training Datasets (3)
common crawl
🔴 2.5/10
general
science
Key Strengths
- •Scale and Accessibility: At 9.5+ petabytes, Common Crawl provides unprecedented scale for training d...
- •Diversity: The dataset captures billions of web pages across multiple domains and content types, ena...
- •Comprehensive Coverage: Despite limitations, Common Crawl attempts to represent the broader web acro...
Considerations
- •Biased Coverage: The crawling process prioritizes frequently linked domains, making content from dig...
- •Large-Scale Problematic Content: Contains significant amounts of hate speech, pornography, violent c...
wikipedia
🟡 5/10
science
multilingual
Key Strengths
- •High-Quality Content: Wikipedia articles are subject to community review, fact-checking, and citatio...
- •Multilingual Coverage: Available in 300+ languages, enabling training of models that understand and ...
- •Structured Knowledge: Articles follow consistent formatting with clear sections, allowing models to ...
Considerations
- •Language Inequality: Low-resource language editions have significantly lower quality, fewer articles...
- •Biased Coverage: Reflects biases in contributor demographics; topics related to Western culture and ...
arxiv
🟡 5.5/10
science
reasoning
Key Strengths
- •Scientific Authority: Peer-reviewed content from established repository
- •Domain-Specific: Specialized vocabulary and concepts
- •Mathematical Content: Includes complex equations and notation
Considerations
- •Specialized: Primarily technical and mathematical content
- •English-Heavy: Predominantly English-language papers
Explore our comprehensive training dataset analysis
View All DatasetsCode Examples
brainwaves
arc arc/e boolq hswag obkqa piqa wino
qx86-hi 0.668,0.833,0.905,0.789,0.486,0.820,0.758
Perplexity
qx86-hi 3.674 ± 0.022
Qwen3.5-27B-Architect-Deckard-Heretic
mxfp4 0.461,0.513,0.821,0.727,0.396,0.777,0.773
Qwen3.5-27B-Text
mxfp4 0.460,0.527,0.871,0.694,0.370,0.772,0.752Model recipetext
models:
- model: DavidAU/Qwen3.5-27B-Deckard-PKD-Heretic-Uncensored-Thinking
parameters:
weight: 1.6
- model: DavidAU/Qwen3.5-27B-Claude-4.6-OS-INSTRUCT
parameters:
weight: 0.4
merge_method: nuslerp
dtype: bfloat16
name: Qwen3.5-27B-Engineer-Deckard-ClaudeDeploy This Model
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