Cotype Nano by MTSAIR

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  Autotrain compatible   Conversational   En   Endpoints compatible   Qwen2   Region:us   Ru   Safetensors
Model Card on HF ๐Ÿค—: https://huggingface.co/MTSAIR/Cotype-Nano 

Cotype Nano Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Cotype Nano (MTSAIR/Cotype-Nano)

Cotype Nano Parameters and Internals

Model Type 
text-generation
Additional Notes 
Cotype-Nano is optimized for fast and efficient interaction with users, providing high performance even under resource-constrained conditions.
Supported Languages 
ru (unknown), en (unknown)
Training Details 
Data Sources:
internal and open synthetic instructional datasets
Methodology:
The model was trained in two stages. In the first stage, MLP layers were trained on mathematics and code. In the second stage, the entire model was trained
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text
LLM NameCotype Nano
Repository ๐Ÿค—https://huggingface.co/MTSAIR/Cotype-Nano 
Model Size1.5b
Required VRAM3.1 GB
Updated2024-12-08
MaintainerMTSAIR
Model Typeqwen2
Model Files  3.1 GB
Supported Languagesru en
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.46.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

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Rank the Cotype Nano Capabilities

๐Ÿ†˜ 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! ๐ŸŒŸ

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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124