LLM EXPLORER
 LLM Explorer: A Curated Large Language Model Directory and Analytics
Dark Theme
  LLM  List    LLM Hosting    LLM Leaderboards    Blog    Newsfeed    Advertise

Phi 3 Mini 128K Instruct LLaMAfied by ThomasComics

 »  All LLMs  »  ThomasComics  »  Phi 3 Mini 128K Instruct LLaMAfied   URL Share it on

  8   
  Autotrain compatible   Code   Conversational   En   Endpoints compatible   Instruct   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/ThomasComics/Phi-3-mini-128k-instruct-LLaMAfied 

Phi 3 Mini 128K Instruct LLaMAfied Benchmarks

LLME Score: 0.1484
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 LLaMAfied (ThomasComics/Phi-3-mini-128k-instruct-LLaMAfied)
🌟 Advertise your project 🚀

Phi 3 Mini 128K Instruct LLaMAfied Parameters and Internals

Model Type 
text-generation, nlp
Use Cases 
Areas:
Commercial, Research
Applications:
Memory/compute constrained environments, Latency bound scenarios, Strong reasoning applications (especially code, math, and logic)
Primary Use Cases:
Building block for generative AI, Acceleration of research on language and multimodal models
Limitations:
Developers should consider common limitations and evaluate for accuracy, safety, and fairness before applying to specific use cases.
Considerations:
The model is not designed for all downstream purposes; adherence to applicable laws is recommended.
Additional Notes 
Phi-3 Mini-4K-Instruct is optimized for GPU, CPU, and Mobile with different configurations, including ONNX models.
Supported Languages 
en (Primary language for use; model performance is optimized for English.)
Training Details 
Data Sources:
Publicly available documents, newly created synthetic "textbook-like" data, supervised data
Data Volume:
3.3T tokens
Methodology:
Supervised fine-tuning and Direct Preference Optimization
Context Length:
4000
Training Time:
7 days
Hardware Used:
512 H100-80G GPUs
Model Architecture:
Dense decoder-only Transformer model with alignment to human preferences and safety guidelines.
Responsible Ai Considerations 
Fairness:
The model's quality of service may vary across different English varieties and non-English languages.
Transparency:
Developers should follow transparency best practices and inform end-users they are interacting with an AI system.
Accountability:
Developers are responsible for ensuring compliance with relevant laws and regulations; assessments for high-risk scenarios recommended.
Mitigation Strategies:
Implement feedback mechanisms and pipelines to ground responses in use-case specific, contextual information.
Input Output 
Input Format:
Best suited for chat format with structured prompts and questions.
Accepted Modalities:
text
Output Format:
Generated text in response to input
LLM NamePhi 3 Mini 128K Instruct LLaMAfied
Repository 🤗https://huggingface.co/ThomasComics/Phi-3-mini-128k-instruct-LLaMAfied 
Model Size3.8b
Required VRAM7.6 GB
Updated2025-09-23
MaintainerThomasComics
Model Typellama
Instruction-BasedYes
Model Files  7.6 GB: 1-of-1
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensemit
Context Length131072
Model Max Length131072
Transformers Version4.40.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token<|endoftext|>
Vocabulary Size32064
Torch Data Typebfloat16

Best Alternatives to Phi 3 Mini 128K Instruct LLaMAfied

Best Alternatives
Context / RAM
Downloads
Likes
Tara 3.8B146K / 7.6 GB50
...hi3 Unlearning General Methode128K / 7.6 GB3550
Superthoughts Mini V1.3.8B128K / 7.6 GB781
Phi 3.5 Mini Instruct128K / 7.6 GB285344
Phi 3 5 Mini Kp 12k Cfr Sft128K / 7.6 GB80
Phi 3 5 Mini Tictactoe1200128K / 7.6 GB50
Llamaphi 3 128K Instruct128K / 7.6 GB101
...i 3 Mini 4K Instruct LLaMAfied4K / 7.6 GB111
Phillama 3.8B V0.14K / 7.6 GB510
Phillama 3.8B V14K / 7.6 GB95
Note: green Score (e.g. "73.2") means that the model is better than ThomasComics/Phi-3-mini-128k-instruct-LLaMAfied.

Rank the Phi 3 Mini 128K Instruct LLaMAfied 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  

What open-source LLMs or SLMs are you in search of? 51545 in total.

Email us: info@extractum.io. Our Privacy Policy  | Terms and Conditions  | Suggest an improvement.
Our Social Media →  
Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
  Support LLM Explorer