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APT3 275M Base by Azurro

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APT3 275M Base is an open-source language model by Azurro. Features: 275m LLM, VRAM: 1.1GB, Context: 2K, License: cc-by-nc-4.0, LLM Explorer Score: 0.13.

  Allamo Dataset:chrisociepa/wikipedia-...   Llama   Pl   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/Azurro/APT3-275M-Base 

APT3 275M Base Benchmarks

LLME Score: 0.12552
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
APT3 275M Base (Azurro/APT3-275M-Base)
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APT3 275M Base Parameters and Internals

Model Type 
causal decoder-only
Use Cases 
Areas:
scientific purposes, private use
Limitations:
not intended for deployment without fine-tuning
Additional Notes 
Not intended for deployment without fine-tuning. It can produce factually incorrect output and should not be relied on for factually accurate information.
Supported Languages 
Polish (native)
Training Details 
Data Sources:
ebooks, Polish Wikipedia, web crawl data
Data Volume:
21 billion tokens
Context Length:
1024
Hardware Used:
Nvidia’s RTX 4090 24GB VRAM
Model Architecture:
transformer
Input Output 
Accepted Modalities:
text
Output Format:
text
LLM NameAPT3 275M Base
Repository 🤗https://huggingface.co/Azurro/APT3-275M-Base 
Model Size275m
Required VRAM1.1 GB
Updated2026-03-29
MaintainerAzurro
Model Typellama
Model Files  0.0 GB   1.1 GB   2.2 GB   1.1 GB
Supported Languagespl
Model ArchitectureLlamaForCausalLM
Licensecc-by-nc-4.0
Context Length2048
Model Max Length2048
Transformers Version4.35.0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size31980
Torch Data Typefloat32

Rank the APT3 275M Base 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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