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Genji Jp by NovelAI

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Genji Jp is an open-source language model by NovelAI. Features: LLM, VRAM: 12.1GB, License: apache-2.0, LLM Explorer Score: 0.

  Arxiv:2104.09864   En   Endpoints compatible   Gptj   Ja   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/NovelAI/genji-jp 

Genji Jp Benchmarks

LLME Score: 0.00228
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Genji Jp (NovelAI/genji-jp)
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Genji Jp Parameters and Internals

Model Type 
causal-lm
Use Cases 
Areas:
Japanese storytelling
Supported Languages 
Japanese (fluent)
Training Details 
Data Sources:
the Pile, Japanese storytelling dataset
Context Length:
2048
Model Architecture:
The model consists of 28 layers, each consisting of one feedforward block and one self-attention block. The model dimension is 4096, feedforward dimension is 16384, using Rotary position encodings (RoPE).
Input Output 
Input Format:
Tokenized text input.
Accepted Modalities:
text
Output Format:
Generated text
Performance Tips:
Ensure correct tokenization and appropriate model parameters like temperature, top_p, etc.
LLM NameGenji Jp
Repository 🤗https://huggingface.co/NovelAI/genji-jp 
Required VRAM12.1 GB
Updated2026-03-13
MaintainerNovelAI
Model Typegptj
Model Files  12.1 GB
Supported Languagesja en
Model ArchitectureGPTJForCausalLM
Licenseapache-2.0
Transformers Version4.10.0.dev0
Tokenizer ClassGPT2Tokenizer
Vocabulary Size50400
Torch Data Typefloat16
Activation Functiongelu_new

Best Alternatives to Genji Jp

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Context / RAM
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Likes
DiffMerge DollyGPT Pygmalion0K / 12.1 GB8532
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Skegma GPTJ0K / 12.3 GB8430
Javalion R0K / 12.3 GB8585
Adventien GPTJ0K / 12.3 GB9000
Javalion GPTJ0K / 12.3 GB8261
Javelin R0K / 12.3 GB8952
Janin GPTJ0K / 12.3 GB8530
Javelin GPTJ0K / 12.3 GB8294
Note: green Score (e.g. "73.2") means that the model is better than NovelAI/genji-jp.

Rank the Genji Jp Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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