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Pythia 31M Simplewiki 2048 by pszemraj

 »  All LLMs  »  pszemraj  »  Pythia 31M Simplewiki 2048   URL Share it on

  2018   
  Autotrain compatible Dataset:pszemraj/simple wikipe...   Endpoints compatible   Generated from trainer   Gpt neox   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/pszemraj/pythia-31m-simplewiki-2048 

Pythia 31M Simplewiki 2048 Benchmarks

ARC: 22.18 vs 96.7 (so35)-77.1%
HellaSwag: 25.55 vs 95.3 (gpt4)-73.2%
MMLU: 23.12 vs 88.3 (so35)-73.8%
TruthfulQA: 49.37 vs 59 (gpt4)-16.3%
WinoGrande: 49.41 vs 87.5 (gpt4)-43.5%
LLME Score: 0.19923
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Pythia 31M Simplewiki 2048 (pszemraj/pythia-31m-simplewiki-2048)

Pythia 31M Simplewiki 2048 Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
baseline comparison
Additional Notes 
More information is needed on certain sections like model description and training data.
Training Details 
Data Sources:
pszemraj/simple_wikipedia_LM
Context Length:
2048
Model Architecture:
Initialized from random weights based on the config of EleutherAI/pythia-31m
LLM NamePythia 31M Simplewiki 2048
Repository 🤗https://huggingface.co/pszemraj/pythia-31m-simplewiki-2048 
Model Size31m
Required VRAM0.1 GB
Updated2025-02-22
Maintainerpszemraj
Model Typegpt_neox
Model Files  0.1 GB   0.0 GB
Model ArchitectureGPTNeoXForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.33.1
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50304
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than pszemraj/pythia-31m-simplewiki-2048.

Rank the Pythia 31M Simplewiki 2048 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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