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Sheared Pythia 160M by princeton-nlp

 »  All LLMs  »  princeton-nlp  »  Sheared Pythia 160M   URL Share it on

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  Arxiv:2310.06694   Autotrain compatible   Endpoints compatible   Gpt neox   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/princeton-nlp/Sheared-Pythia-160m 

Sheared Pythia 160M Benchmarks

ARC: 22.44 vs 96.7 (so35)-76.8%
HellaSwag: 32.07 vs 95.3 (gpt4)-66.3%
MMLU: 26.65 vs 88.3 (so35)-69.8%
TruthfulQA: 43.22 vs 59 (gpt4)-26.7%
WinoGrande: 51.7 vs 87.5 (gpt4)-40.9%
GSM8K: 0.38 vs 96.4 (so35)-99.6%
LLME Score: 0.199
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Sheared Pythia 160M (princeton-nlp/Sheared-Pythia-160m)

Sheared Pythia 160M Parameters and Internals

Model Type 
text generation
Training Details 
Data Sources:
The Pile dataset
Data Volume:
0.4B tokens for pruning and 50B tokens for continued pre-training
Methodology:
Structured pruning
Model Architecture:
GPT-NeoX
LLM NameSheared Pythia 160M
Repository 🤗https://huggingface.co/princeton-nlp/Sheared-Pythia-160m 
Model Size160m
Required VRAM0.7 GB
Updated2025-02-05
Maintainerprinceton-nlp
Model Typegpt_neox
Model Files  0.7 GB
Model ArchitectureGPTNeoXForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.28.1
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50304
Torch Data Typefloat32

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... Llm Pythia 160M Pm Gen Ian Nd2K / 0.6 GB1340
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Note: green Score (e.g. "73.2") means that the model is better than princeton-nlp/Sheared-Pythia-160m.

Rank the Sheared Pythia 160M Capabilities

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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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