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Gptj 162M by architext

 »  All LLMs  »  architext  »  Gptj 162M   URL Share it on

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  Arxiv:2303.07519   Architecture   Autotrain compatible   Dataset:theodoros/architext v1   Design   En   Endpoints compatible   Gptj   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/architext/gptj-162M 

Gptj 162M Benchmarks

LLME Score: 0.03514
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gptj 162M (architext/gptj-162M)
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Gptj 162M Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
research, commercial applications
Primary Use Cases:
generating residential floor plans
Limitations:
primarily limited to residential layouts, may generate semantically incorrect designs
Considerations:
These are conceptual designs and should not be used directly for construction.
Additional Notes 
The model uses a tokenization vocabulary of 50257 with a BPEs set the same as GPT-2/GPT-3.
Supported Languages 
en (English)
Training Details 
Data Sources:
the Pile, synthetically generated data
Methodology:
The model was finetuned for 1.25 billion tokens over 11,500 steps on TPU v3-8, as an autoregressive language model, using cross-entropy loss.
Hardware Used:
TPU v3-8
Model Architecture:
Transformer model with 12 layers, model dimension of 768, and feedforward dimension of 2048, split into 16 heads with a dimension of 256 each. Rotary Position Embedding (RoPE) is applied to 64 dimensions of each head.
LLM NameGptj 162M
Repository 🤗https://huggingface.co/architext/gptj-162M 
Model Size162m
Required VRAM0.3 GB
Updated2025-09-26
Maintainerarchitext
Model Typegptj
Model Files  0.3 GB
Supported Languagesen
Model ArchitectureGPTJForCausalLM
Licenseapache-2.0
Model Max Length2048
Transformers Version4.22.2
Tokenizer ClassGPT2Tokenizer
Beginning of Sentence Token<|endoftext|>
End of Sentence Token<|endoftext|>
Unk Token<|endoftext|>
Vocabulary Size50400
Torch Data Typefloat16
Activation Functiongelu_new
Errorsreplace

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Rank the Gptj 162M 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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