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Phi 3 Mini 128K Instruct Ov Fp16 Int4 Asym by nsbendre25

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Model Card on HF 🤗: https://huggingface.co/nsbendre25/Phi-3-mini-128k-instruct-ov-fp16-int4-asym 

Phi 3 Mini 128K Instruct Ov Fp16 Int4 Asym Benchmarks

LLME Score: 0.18501
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 128K Instruct Ov Fp16 Int4 Asym (nsbendre25/Phi-3-mini-128k-instruct-ov-fp16-int4-asym)

Phi 3 Mini 128K Instruct Ov Fp16 Int4 Asym Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
research, commercial applications
Primary Use Cases:
advanced natural language understanding and generation tasks
Limitations:
Not intended for use in creating or promoting harmful or illegal content
Additional Notes 
The model is optimized using OpenVINO for devices with limited computational power through weight compression using the INT4_ASYM mode.
LLM NamePhi 3 Mini 128K Instruct Ov Fp16 Int4 Asym
Repository 🤗https://huggingface.co/nsbendre25/Phi-3-mini-128k-instruct-ov-fp16-int4-asym 
Base Model(s)  ...i 3 Mini 128K Instruct Ov Int4   fakezeta/Phi-3-mini-128k-instruct-ov-int4
Required VRAM2.5 GB
Updated2025-01-28
Maintainernsbendre25
Model Typephi3
Instruction-BasedYes
Model Files  2.5 GB
Supported Languagesen
Quantization Typefp16
Model ArchitecturePhi3ForCausalLM
Licensemit
Context Length131072
Model Max Length131072
Transformers Version4.37.2
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 nsbendre25/Phi-3-mini-128k-instruct-ov-fp16-int4-asym.

Rank the Phi 3 Mini 128K Instruct Ov Fp16 Int4 Asym 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 v20241227
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