EleutherAI GPT Neo 2.7B 4bits by RichardErkhov

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  Arxiv:2101.00027   4-bit   Autotrain compatible   Bitsandbytes   Endpoints compatible   Gpt neo   Pytorch   Region:us   Safetensors

EleutherAI GPT Neo 2.7B 4bits Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
EleutherAI GPT Neo 2.7B 4bits (RichardErkhov/EleutherAI_-_gpt-neo-2.7B-4bits)

EleutherAI GPT Neo 2.7B 4bits Parameters and Internals

Model Type 
text generation, causal-lm
Use Cases 
Areas:
Research, Commercial applications
Applications:
Text generation
Primary Use Cases:
Generating text from a prompt
Limitations:
Potentially socially unacceptable text, biases from training dataset
Considerations:
Human curation recommended to improve quality and censor undesirable content.
Supported Languages 
languages_supported (en), proficiency_level (fluent)
Training Details 
Data Sources:
EleutherAI/pile
Data Volume:
800GB
Methodology:
Masked autoregressive language model with cross-entropy loss
Training Time:
420 billion tokens over 400,000 steps
Model Architecture:
Transformer based architecture replicating GPT-3
Safety Evaluation 
Ethical Considerations:
Model may produce socially unacceptable text; filtering recommended.
Responsible Ai Considerations 
Mitigation Strategies:
Human curation or filtering of outputs is recommended to censor undesirable content and improve result quality.
Input Output 
Input Format:
text input for text generation
Accepted Modalities:
text
Output Format:
generated text
LLM NameEleutherAI GPT Neo 2.7B 4bits
Repository ๐Ÿค—https://huggingface.co/RichardErkhov/EleutherAI_-_gpt-neo-2.7B-4bits 
Model Size2.7b
Required VRAM1.7 GB
Updated2024-12-26
MaintainerRichardErkhov
Model Typegpt_neo
Model Files  1.7 GB
Supported Languagesen
Model ArchitectureGPTNeoForCausalLM
Licensemit
Context Length2048
Model Max Length2048
Transformers Version4.39.3
Tokenizer ClassGPT2Tokenizer
Vocabulary Size50257
Torch Data Typefloat16
Activation Functiongelu_new
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than RichardErkhov/EleutherAI_-_gpt-neo-2.7B-4bits.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217