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Phi 3 Mini 4K Instruct by pranavthombare

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Model Card on HF 🤗: https://huggingface.co/pranavthombare/Phi-3-mini-4k-instruct 

Phi 3 Mini 4K Instruct Benchmarks

LLME Score: 0.19401
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 (pranavthombare/Phi-3-mini-4k-instruct)

Phi 3 Mini 4K Instruct Parameters and Internals

Model Type 
text-generation, code
Use Cases 
Areas:
commercial, research
Applications:
Memory/compute constrained environments, Latency bound scenarios, Strong reasoning (code, math, logic)
Primary Use Cases:
generative AI powered features
Limitations:
Not specifically designed for all downstream purposes
Considerations:
Developers should be aware of and adhere to applicable laws or regulations.
Additional Notes 
The model uses flash attention by default.
Supported Languages 
en (high)
Training Details 
Data Sources:
Publicly available documents, educational data, code, synthetic, "textbook-like" data
Data Volume:
3.3 trillion tokens
Methodology:
Supervised fine-tuning (SFT) and Direct Preference Optimization (DPO)
Context Length:
4000
Training Time:
7 days
Hardware Used:
512 H100-80G GPUs
Model Architecture:
Dense decoder-only Transformer model
Safety Evaluation 
Ethical Considerations:
Like other language models, the Phi series models can potentially behave in ways that are unfair, unreliable, or offensive.
Responsible Ai Considerations 
Fairness:
Models can over- or under-represent groups of people, erase representation of some groups, or reinforce demeaning or negative stereotypes.
Accountability:
Developers should apply responsible AI best practices and ensure compliance with relevant laws.
Mitigation Strategies:
Safety post-training and responsible AI best practices.
Input Output 
Input Format:
Text, best suited for prompts using chat format.
Accepted Modalities:
text
Output Format:
Generated text
LLM NamePhi 3 Mini 4K Instruct
Repository 🤗https://huggingface.co/pranavthombare/Phi-3-mini-4k-instruct 
Model Size3.8b
Required VRAM7.7 GB
Updated2025-02-22
Maintainerpranavthombare
Model Typephi3
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   2.7 GB: 2-of-2
Supported Languagesen
Model ArchitecturePhi3ForCausalLM
Licensemit
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 pranavthombare/Phi-3-mini-4k-instruct.

Rank the Phi 3 Mini 4K Instruct 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 v20241227
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