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TinyStories 1M by roneneldan

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TinyStories 1M is an open-source language model by roneneldan. Features: 1m LLM, Context: 2K, LLM Explorer Score: 0.18, Arc: 23.5, HellaSwag: 25.2, MMLU: 24.6.

  Arxiv:2305.07759   Dataset:roneneldan/tinystories   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%
LLME Score: 0.18255
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)
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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
Updated2026-07-13
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

Best Alternatives to TinyStories 1M

Best Alternatives
Context / RAM
Downloads
Likes
IllaryiaStories 1M2K / 0 GB660
Mia Astral 1.32B Conv2K / 5.3 GB50
Complexity 1B2K / 2.6 GB51
TinyStories 1M Ds2K /  GB1630
TinyStories 1M ONNX2K /  GB82
TinyStories Instruct 1M2K / 0 GB17874
...n Prompt Generator 1M Examples2K / 0.6 GB124
Skript 1M GPT Neo350m2K / 0 GB81
Skript 1M GPT Neo125m2K / 0.6 GB60
Note: green Score (e.g. "73.2") means that the model is better than roneneldan/TinyStories-1M.

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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