GPT Neo 2.7B by EleutherAI

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  Arxiv:2101.00027   Autotrain compatible   Dataset:eleutherai/pile   En   Endpoints compatible   Gpt neo   Jax   Pytorch   Region:us   Rust   Safetensors
Model Card on HF ๐Ÿค—: https://huggingface.co/EleutherAI/gpt-neo-2.7B 

GPT Neo 2.7B Benchmarks

GPT Neo 2.7B (EleutherAI/gpt-neo-2.7B)

GPT Neo 2.7B Parameters and Internals

Model Type 
text generation, causal-lm
Use Cases 
Areas:
research, commercial applications
Applications:
text generation, language processing
Primary Use Cases:
generating texts from a prompt
Limitations:
unknown outputs, socially unacceptable text potential
Considerations:
Intent to improve results with human curation/filtering.
Supported Languages 
English (proficient)
Training Details 
Data Sources:
EleutherAI/pile
Data Volume:
420 billion tokens
Methodology:
masked autoregressive
Model Architecture:
transformer
Responsible Ai Considerations 
Fairness:
depends on Pile's dataset content
Transparency:
unknown biases in training data
Accountability:
Users are advised to curate outputs
Mitigation Strategies:
Human curation recommended
Input Output 
Input Format:
text prompt
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Use text-generation pipeline for generation
LLM NameGPT Neo 2.7B
Repository ๐Ÿค—https://huggingface.co/EleutherAI/gpt-neo-2.7B 
Model Size2.7b
Required VRAM10.7 GB
Updated2025-02-05
MaintainerEleutherAI
Model Typegpt_neo
Model Files  10.7 GB   10.7 GB
Supported Languagesen
Model ArchitectureGPTNeoForCausalLM
Licensemit
Context Length2048
Model Max Length2048
Transformers Version4.9.0.dev0
Tokenizer ClassGPT2Tokenizer
Vocabulary Size50257
Activation Functiongelu_new

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Note: green Score (e.g. "73.2") means that the model is better than EleutherAI/gpt-neo-2.7B.

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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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227