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Phi 3 Mini 4K Instruct Function Calling by mzbac

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Phi 3 Mini 4K Instruct Function Calling is an open-source language model by mzbac. Features: 3.8b LLM, VRAM: 7.7GB, Context: 4K, Instruction-Based, LLM Explorer Score: 0.13.

  Autotrain compatible   Conversational   Custom code Dataset:mzbac/function-calling...   Endpoints compatible   Instruct   Phi3   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/mzbac/Phi-3-mini-4k-instruct-function-calling 

Phi 3 Mini 4K Instruct Function Calling Benchmarks

LLME Score: 0.13431
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Phi 3 Mini 4K Instruct Function Calling (mzbac/Phi-3-mini-4k-instruct-function-calling)
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Phi 3 Mini 4K Instruct Function Calling Parameters and Internals

Model Type 
Causal Language Model
Additional Notes 
This model is fine-tuned specifically for function calling tasks within conversational contexts.
Training Details 
Data Sources:
mzbac/function-calling-phi-3-format-v1.1
Methodology:
Fine-tuning with LoRA layers.
Context Length:
4096
Input Output 
Input Format:
Tokenized user prompts using a specific chat template format.
Accepted Modalities:
text
Output Format:
Generated responses based on prompts including function call instructions.
LLM NamePhi 3 Mini 4K Instruct Function Calling
Repository 🤗https://huggingface.co/mzbac/Phi-3-mini-4k-instruct-function-calling 
Model Size3.8b
Required VRAM7.7 GB
Updated2025-11-16
Maintainermzbac
Model Typephi3
Instruction-BasedYes
Model Files  5.4 GB: 1-of-2   2.3 GB: 2-of-2
Model ArchitecturePhi3ForCausalLM
Context Length4096
Model Max Length4096
Transformers Version4.39.3
Tokenizer ClassLlamaTokenizer
Padding Token<|endoftext|>
Vocabulary Size32064
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than mzbac/Phi-3-mini-4k-instruct-function-calling.

Rank the Phi 3 Mini 4K Instruct 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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