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Javelin GPTJ by digitous

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  Autotrain compatible   Endpoints compatible   Gptj   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/digitous/Javelin-GPTJ 

Javelin GPTJ Benchmarks

ARC: 42.66 vs 96.7 (so35)-55.9%
HellaSwag: 70.45 vs 95.3 (gpt4)-26.1%
MMLU: 26.2 vs 88.3 (so35)-70.3%
TruthfulQA: 36.08 vs 59 (gpt4)-38.8%
WinoGrande: 64.17 vs 87.5 (gpt4)-26.7%
GSM8K: 1.82 vs 96.4 (so35)-98.1%
LLME Score: 0.12368
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Javelin GPTJ (digitous/Javelin-GPTJ)
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Javelin GPTJ Parameters and Internals

Additional Notes 
This 4x merge is not intended for minors, as it can produce NC-17+ content (mostly from Shinen).
LLM NameJavelin GPTJ
Repository 🤗https://huggingface.co/digitous/Javelin-GPTJ 
Required VRAM12.3 GB
Updated2025-08-17
Maintainerdigitous
Model Typegptj
Model Files  2.1 GB: 1-of-6   2.1 GB: 2-of-6   2.1 GB: 3-of-6   2.1 GB: 4-of-6   2.0 GB: 5-of-6   1.9 GB: 6-of-6
Model ArchitectureGPTJForCausalLM
Licensecreativeml-openrail-m
Model Max Length2048
Transformers Version4.24.0
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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Note: green Score (e.g. "73.2") means that the model is better than digitous/Javelin-GPTJ.

Rank the Javelin GPTJ 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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