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GPT Neo Pt Br by josu

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  Autotrain compatible   Endpoints compatible   Gpt neo   Pt   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/josu/gpt-neo-pt-br 

GPT Neo Pt Br Benchmarks

LLME Score: 0.07009
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
GPT Neo Pt Br (josu/gpt-neo-pt-br)
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GPT Neo Pt Br Parameters and Internals

Model Type 
Causal Language Model, Text Generation
Use Cases 
Areas:
Research, Development
Applications:
Text generation in Portuguese, Chatbots, Content creation
Primary Use Cases:
Portuguese language models
Supported Languages 
Portuguese (High proficiency)
Training Details 
Data Sources:
Portuguese corpora, web text
Methodology:
Trained with causal language modeling techniques
Model Architecture:
GPT-Neo
Input Output 
Input Format:
Plain text in Portuguese
Accepted Modalities:
Text
Output Format:
Generated Portuguese text
LLM NameGPT Neo Pt Br
Repository 🤗https://huggingface.co/josu/gpt-neo-pt-br 
Required VRAM0.6 GB
Updated2025-09-23
Maintainerjosu
Model Typegpt_neo
Model Files  0.6 GB
Supported Languagespt
Model ArchitectureGPTNeoForCausalLM
Context Length2048
Model Max Length2048
Transformers Version4.26.1
Tokenizer ClassGPT2Tokenizer
Beginning of Sentence Token<|endoftext|>
End of Sentence Token<|endoftext|>
Unk Token<|endoftext|>
Vocabulary Size50257
Torch Data Typefloat32
Activation Functiongelu_new
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than josu/gpt-neo-pt-br.

Rank the GPT Neo Pt Br 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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Release v20241124
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