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TinyStories 1M by roneneldan

 »  All LLMs  »  roneneldan  »  TinyStories 1M   URL Share it on

  41420   
  Arxiv:2305.07759   Autotrain compatible   Endpoints compatible   Gpt neo   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/roneneldan/TinyStories-1M 

TinyStories 1M Benchmarks

ARC: 23.46 vs 96.7 (so35)-75.7%
HellaSwag: 25.23 vs 95.3 (gpt4)-73.5%
MMLU: 24.57 vs 88.3 (so35)-72.2%
TruthfulQA: 49.4 vs 59 (gpt4)-16.3%
WinoGrande: 52.17 vs 87.5 (gpt4)-40.4%
LLME Score: 0.20814
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TinyStories 1M (roneneldan/TinyStories-1M)

TinyStories 1M Parameters and Internals

Model Type 
text generation
Training Details 
Data Sources:
TinyStories Dataset
Input Output 
Input Format:
Tokens encoded using AutoTokenizer
Accepted Modalities:
text
Output Format:
Decoded text output by AutoTokenizer
LLM NameTinyStories 1M
Repository 🤗https://huggingface.co/roneneldan/TinyStories-1M 
Model Size1m
Required VRAM0 GB
Updated2025-02-22
Maintainerroneneldan
Model Typegpt_neo
Model Files  0.0 GB
Model ArchitectureGPTNeoForCausalLM
Context Length2048
Model Max Length2048
Transformers Version4.28.0
Tokenizer ClassGPT2Tokenizer
Beginning of Sentence Token<|endoftext|>
End of Sentence Token<|endoftext|>
Unk Token<|endoftext|>
Vocabulary Size50257
Torch Data Typefloat32
Activation Functiongelu_new
Errorsreplace

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Rank the TinyStories 1M 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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