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CSUMLM by Or4cl3-1

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Model Card on HF 🤗: https://huggingface.co/Or4cl3-1/CSUMLM 

CSUMLM Benchmarks

LLME Score: 0.16013
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
CSUMLM (Or4cl3-1/CSUMLM)

CSUMLM Parameters and Internals

Model Type 
text generation, multimodal processing
Use Cases 
Applications:
Natural Language Processing, Multimodal Understanding, Real-time Applications, Research and Development
Limitations:
Data Requirements, Computational Resources, Bias and Fairness
Training Details 
Methodology:
Hybrid learning engine with transfer learning, deep learning, self-supervised learning, meta-learning, deep meta-learning, reinforcement learning, and cross-domain analogy extraction
Model Architecture:
Advanced attention mechanism combining traditional attention, self-attention, and linear attention with a hierarchical belief desire intent tree/chain of thought structure
LLM NameCSUMLM
Repository 🤗https://huggingface.co/Or4cl3-1/CSUMLM 
Model NameCognoSphere/CSUMLM
Updated2025-02-22
MaintainerOr4cl3-1
Model Typeencoder_decoder
Instruction-BasedYes
Supported Languagesen
Model ArchitectureAutoModel
Licenseapache-2.0
Vocabulary Size32000

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Note: green Score (e.g. "73.2") means that the model is better than Or4cl3-1/CSUMLM.

Rank the CSUMLM Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Release v20241227
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