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Rabbit Ko 15B Instruct by CarrotAI

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Base model:finetune:qwen/qwen2... Base model:qwen/qwen2-7b-instr...   Carrot   Conversational Dataset:carrotai/amazing-instr... Dataset:carrotai/ko-instructio...   Dataset:carrotai/kommlu   Instruct   Ko   Korea   Mergekit   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/CarrotAI/Rabbit-Ko-15B-Instruct 

Rabbit Ko 15B Instruct Benchmarks

LLME Score: 0.24847
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Rabbit Ko 15B Instruct (CarrotAI/Rabbit-Ko-15B-Instruct)

Rabbit Ko 15B Instruct Parameters and Internals

Model Type 
text-generation
Use Cases 
Primary Use Cases:
chatbots, question-answering systems
Limitations:
Performance can vary based on task complexity and input specifics.
Considerations:
Users should evaluate the model thoroughly in their specific context.
Additional Notes 
Model is trained using Singleton data.
Supported Languages 
ko (proficient)
Training Details 
Data Sources:
CarrotAI/ko-instruction-dataset, CarrotAI/Amazing-Instructions, CarrotAI/kommlu
Methodology:
Fine-tuning
Model Architecture:
Qwen2ForCausalLM
LLM NameRabbit Ko 15B Instruct
Repository 🤗https://huggingface.co/CarrotAI/Rabbit-Ko-15B-Instruct 
Base Model(s)  Qwen2 7B Instruct   Qwen/Qwen2-7B-Instruct
Model Size7b
Required VRAM30.1 GB
Updated2024-12-21
MaintainerCarrotAI
Model Typeqwen2
Instruction-BasedYes
Model Files  4.9 GB: 1-of-7   4.9 GB: 2-of-7   5.0 GB: 3-of-7   5.0 GB: 4-of-7   4.9 GB: 5-of-7   4.3 GB: 6-of-7   1.1 GB: 7-of-7
Supported Languagesko
Model ArchitectureQwen2ForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.44.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typefloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than CarrotAI/Rabbit-Ko-15B-Instruct.

Rank the Rabbit Ko 15B Instruct 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217
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