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Phi 3 Mini 128K Instruct by inventbot

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Phi 3 Mini 128K Instruct is an open-source language model by inventbot. Features: 3.8b LLM, VRAM: 7.7GB, Context: 128K, License: mit, Instruction-Based, LLM Explorer Score: 0.24, ELO: 1128.

  Autotrain compatible   Code   Conversational   Custom code   En   Endpoints compatible   Instruct   Phi3   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/inventbot/Phi-3-mini-128k-instruct 

Phi 3 Mini 128K Instruct Benchmarks

LMSys ELO: 1128 vs 1272 (so35)-11.3%
LLME Score: 0.24145
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 (inventbot/Phi-3-mini-128k-instruct)
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Phi 3 Mini 128K Instruct Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Commercial and research use in English, 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:
Evaluate and mitigate for accuracy, safety, and fairness before use in high-risk scenarios.
Additional Notes 
The model uses flash attention which requires certain types of GPU hardware.
Supported Languages 
en (Primary language supported)
Training Details 
Data Sources:
Publicly available documents filtered rigorously for quality, Selected high-quality educational data, Code, Newly created synthetic "textbook-like" data, High quality chat format supervised data covering various topics
Data Volume:
3.3T tokens
Methodology:
Supervised fine-tuning and Direct Preference Optimization
Context Length:
128000
Training Time:
7 days
Hardware Used:
512 H100-80G GPUs
Model Architecture:
Dense decoder-only Transformer model
Safety Evaluation 
Methodologies:
Safety post-training
Risk Categories:
Misinformation, Bias, Inappropriate or Offensive Content
Ethical Considerations:
Developers should apply responsible AI best practices and are responsible for ensuring compliance with relevant laws.
Responsible Ai Considerations 
Fairness:
Models can potentially behave in ways that are unfair.
Transparency:
Models can generate nonsensical content or fabricate content.
Accountability:
Developers should assess suitability for high-risk scenarios.
Mitigation Strategies:
Using Retrieval Augmented Generation (RAG) and feedback mechanisms.
Input Output 
Input Format:
Chat format
Accepted Modalities:
text
Output Format:
Generated text in response to input
Performance Tips:
Use the chat format for better results with the provided template.
LLM NamePhi 3 Mini 128K Instruct
Repository 🤗https://huggingface.co/inventbot/Phi-3-mini-128k-instruct 
Model Size3.8b
Required VRAM7.7 GB
Updated2025-09-23
Maintainerinventbot
Model Typephi3
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   2.7 GB: 2-of-2
Supported Languagesen
Model ArchitecturePhi3ForCausalLM
Licensemit
Context Length131072
Model Max Length131072
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 inventbot/Phi-3-mini-128k-instruct.

Rank the Phi 3 Mini 128K Instruct Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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