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Vi Gemma 2 2B Function Calling by ricepaper

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  4bit   Autotrain compatible Base model:finetune:unsloth/ge... Base model:unsloth/gemma-2-2b-...   Conversational   En   Endpoints compatible   Gemma2   Quantized   Region:us   Safetensors   Sharded   Tensorflow   Trl   Unsloth   Vn
Model Card on HF 🤗: https://huggingface.co/ricepaper/vi-gemma-2-2b-function-calling 

Vi Gemma 2 2B Function Calling Benchmarks

LLME Score: 0.22144
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Vi Gemma 2 2B Function Calling (ricepaper/vi-gemma-2-2b-function-calling)

Vi Gemma 2 2B Function Calling Parameters and Internals

Model Type 
text-generation-inference, transformers
Use Cases 
Areas:
commercial applications, research
Applications:
chatbots, automated question answering systems, advanced natural language processing applications
Primary Use Cases:
function call execution, natural language processing tasks such as text summarization and machine translation, creating intelligent agents and multi-agent systems
Additional Notes 
The model leverages Unsloth and Huggingface's TRL library for faster training and execution.
Supported Languages 
vietnamese (optimal), english (optimal)
Training Details 
Methodology:
The model was fine-tuned from google/gemma-2-2b-it using a dataset rich in function-call format conversations (ChatML) and multilingual data translated to Vietnamese.
Input Output 
Input Format:
ChatML format with user queries
Accepted Modalities:
text
Output Format:
Function call execution results and responses
Performance Tips:
Adjust generate parameters for varying response lengths and content
LLM NameVi Gemma 2 2B Function Calling
Repository 🤗https://huggingface.co/ricepaper/vi-gemma-2-2b-function-calling 
Base Model(s)  Gemma 2 2B It Bnb 4bit   unsloth/gemma-2-2b-it-bnb-4bit
Model Size2b
Required VRAM5.2 GB
Updated2024-12-21
Maintainerricepaper
Model Typegemma2
Model Files  5.0 GB: 1-of-2   0.2 GB: 2-of-2
Supported Languagesvn en
Quantization Type4bit
Model ArchitectureGemma2ForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.43.3
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than ricepaper/vi-gemma-2-2b-function-calling.

Rank the Vi Gemma 2 2B Function Calling 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217
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