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Kanarya 2B by asafaya

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  Autotrain compatible   Dataset:mc4   Dataset:oscar   Endpoints compatible   Gptj   Jax   Pytorch   Region:us   Safetensors   Tr
Model Card on HF 🤗: https://huggingface.co/asafaya/kanarya-2b 

Kanarya 2B Benchmarks

LLME Score: 0.16096
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Kanarya 2B (asafaya/kanarya-2b)
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Kanarya 2B Parameters and Internals

Model Type 
text generation
Use Cases 
Primary Use Cases:
fine-tuning on a wide range of Turkish NLP tasks, text generation, translation, summarization
Limitations:
The model may generate toxic, biased, or unethical content.
Considerations:
This model is not intended to be used for any downstream tasks without fine-tuning.
Supported Languages 
Turkish (Native)
Training Details 
Data Sources:
OSCAR, mC4
Context Length:
2048
Hardware Used:
TUBITAK ULAKBIM, High Performance and Grid Computing Center (TRUBA)
Model Architecture:
JAX/Flax implementation of GPT-J
Responsible Ai Considerations 
Mitigation Strategies:
It is highly recommended to use the model responsibly and make sure that the generated content is appropriate for the use case.
LLM NameKanarya 2B
Repository 🤗https://huggingface.co/asafaya/kanarya-2b 
Model Size2b
Required VRAM4.1 GB
Updated2025-09-23
Maintainerasafaya
Model Typegptj
Model Files  4.1 GB   4.1 GB
Supported Languagestr
Model ArchitectureGPTJForCausalLM
Licenseapache-2.0
Model Max Length2048
Transformers Version4.37.2
Tokenizer ClassGPT2Tokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32768
Torch Data Typebfloat16
Activation Functiongelu_new
Errorsreplace

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Rank the Kanarya 2B Capabilities

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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 v20241124
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