Phi 3 Mini 4K CodeInstruct by actualbrain

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Phi 3 Mini 4K CodeInstruct Benchmarks

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 CodeInstruct Parameters and Internals

LLM NamePhi 3 Mini 4K CodeInstruct
Repository ๐Ÿค—https://huggingface.co/actualbrain/Phi-3-mini-4k-CodeInstruct 
Base Model(s)  ...hi 3 Mini 4K Instruct Bnb 4bit   unsloth/Phi-3-mini-4k-instruct-bnb-4bit
Required VRAM7.6 GB
Updated2024-09-01
Maintaineractualbrain
Instruction-BasedYes
Model Files  0.1 GB   5.0 GB: 1-of-2   2.6 GB: 2-of-2
Supported Languagesen
Quantization Type4bit
Model ArchitectureAutoModelForCausalLM
Licenseapache-2.0
Model Max Length4096
Is Biasednone
Tokenizer ClassLlamaTokenizer
Padding Token<|placeholder6|>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesdown_proj|q_proj|v_proj|k_proj|up_proj|gate_proj|o_proj
LoRA Alpha32
LoRA Dropout0.05
R Param16
Phi 3 Mini 4K CodeInstruct (actualbrain/Phi-3-mini-4k-CodeInstruct)

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

Rank the Phi 3 Mini 4K CodeInstruct 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 v2024072803