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GPT Sw3 356M by AI-Sweden-Models

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GPT Sw3 356M is an open-source language model by AI-Sweden-Models. Features: 356m LLM, VRAM: 1.6GB, License: other, HF Score: 30.4, LLM Explorer Score: 0.12, Arc: 23.6, HellaSwag: 37.1, MMLU: 25.9, TruthfulQA: 42.6, WinoGrande: 53, GSM8K: 0.2.

  Da   En   Endpoints compatible   Gpt2   Is   No   Pytorch   Region:us   Safetensors   Sv
Model Card on HF 🤗: https://huggingface.co/AI-Sweden-Models/gpt-sw3-356m 

GPT Sw3 356M Benchmarks

ARC: 23.63 vs 96.7 (so35)-75.6%
HellaSwag: 37.05 vs 95.3 (gpt4)-61.1%
MMLU: 25.93 vs 88.3 (so35)-70.6%
TruthfulQA: 42.55 vs 59 (gpt4)-27.9%
WinoGrande: 53.04 vs 87.5 (gpt4)-39.4%
GSM8K: 0.23 vs 96.4 (so35)-99.8%
LLME Score: 0.11728
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
GPT Sw3 356M (AI-Sweden-Models/gpt-sw3-356m)
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GPT Sw3 356M Parameters and Internals

Model Type 
decoder-only, transformer, language model
Use Cases 
Areas:
Research, Evaluation of Large Language Models in Nordic languages
Limitations:
Bias and safety limitations, Possible content inaccuracies and irrelevance, Generation diversity issues, Potential for generating offensive, inappropriate content
Considerations:
Includes data diversity concerns and requires feedback mechanism for affected individuals.
Supported Languages 
languages_supported (da, sv, no, en, is), proficiency_level (fluent)
Training Details 
Data Sources:
Books from Litteraturbanken, The Pile, Articles from Diva, The Pile: PubMed, The Pile: ArXiv, Code from Code Parrot: Github, Pushshift.io Reddit dataset, English Math dataset, Swedish Math dataset, Summarization data, OPUS, Movie scripts, Natural Instructions, P3, The Norwegian Colossal Corpus, Danish Gigaword, Icelandic Gigaword, The Pile: Stack Exchange, Web Common Crawl, MC4, OSCAR, Open Web Text, Miscellaneous public Swedish websites, Familjeliv Articles, Public Swedish Job Ads, Wikipedia
Data Volume:
1.1TB UTF-8 encoded text
Methodology:
Pretrained using a causal language modeling objective
Model Architecture:
NeMo Megatron GPT
Responsible Ai Considerations 
Fairness:
The model has limitations regarding bias and safety.
Transparency:
Communication and transparency around usage is encouraged.
Mitigation Strategies:
Controlled pre-release; feedback collection from Nordic NLP ecosystem.
Release Notes 
Version:
Second generation
Date:
2022-12-20
LLM NameGPT Sw3 356M
Repository 🤗https://huggingface.co/AI-Sweden-Models/gpt-sw3-356m 
Model Size356m
Required VRAM1.6 GB
Updated2026-04-01
MaintainerAI-Sweden-Models
Model Typegpt2
Model Files  1.6 GB   1.6 GB
Supported Languagesda sv no en is
Model ArchitectureGPT2LMHeadModel
Licenseother
Transformers Version4.25.0.dev0
Tokenizer ClassGPTSw3Tokenizer
Vocabulary Size64000
Torch Data Typefloat32
Activation Functiongelu

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Note: green Score (e.g. "73.2") means that the model is better than AI-Sweden-Models/gpt-sw3-356m.

Rank the GPT Sw3 356M 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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