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APT3 500M Base by Azurro

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  Allamo   Autotrain compatible Dataset:chrisociepa/wikipedia-...   Llama   Pl   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/Azurro/APT3-500M-Base 

APT3 500M Base Benchmarks

LLME Score: 0.14411
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
APT3 500M Base (Azurro/APT3-500M-Base)

APT3 500M Base Parameters and Internals

Model Type 
causal decoder-only
Use Cases 
Areas:
Research, Non-commercial applications
Limitations:
Not intended for deployment without fine-tuning. Not for human-facing interactions without further guardrails and user consent. Can produce factually incorrect outputs.
Additional Notes 
APT3-500M-Base is trained with Polish corpus prioritizing high-quality, manually selected texts over large-scale, lower quality datasets.
Supported Languages 
pl (native)
Training Details 
Data Sources:
ebooks, Polish Wikipedia, web crawl data
Data Volume:
Over 20 billion tokens
Context Length:
1024
Hardware Used:
Nvidia's RTX 4090 24GB VRAM
Model Architecture:
Transformer-based, similar to Meta AI’s LLaMA
Input Output 
Performance Tips:
Use smaller precision (`bfloat16`) to reduce memory usage.
LLM NameAPT3 500M Base
Repository 🤗https://huggingface.co/Azurro/APT3-500M-Base 
Model Size500m
Required VRAM1.9 GB
Updated2025-03-13
MaintainerAzurro
Model Typellama
Model Files  0.0 GB   1.9 GB   3.8 GB   1.9 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

Best Alternatives to APT3 500M Base

Best Alternatives
Context / RAM
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Acheron D8K / 1 GB190
Acheron C8K / 1 GB130
H2o Danube3 500M Chat8K / 1 GB194934
Text Arco8K / 1 GB320
Acheron8K / 1 GB180
H2o Danube3 500M Base8K / 1 GB86430
Arco Plus8K / 1.6 GB686
Danube Reasoner8K / 1 GB640
Clite 500M8K / 1 GB1703
Massive8K / 1 GB1640
Note: green Score (e.g. "73.2") means that the model is better than Azurro/APT3-500M-Base.

Rank the APT3 500M Base 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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Release v20241227
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