Gemma2 Gutenberg 9B by nbeerbower

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Gemma2 Gutenberg 9B is an open-source language model by nbeerbower. Features: 9b LLM, VRAM: 18.6GB, Context: 8K, License: gemma, LLM Explorer Score: 0.21.

Base model:finetune:ucla-agi/g... Base model:ucla-agi/gemma-2-9b...   Conversational Dataset:jondurbin/gutenberg-dp...   Deploy:azure   Endpoints compatible   Gemma2   Model-index   Region:us   Safetensors   Sharded   Tensorflow

Gemma2 Gutenberg 9B Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Gemma2 Gutenberg 9B Parameters and Internals

Model Type 
text-generation
Additional Notes 
Average performance across benchmarks is 22.61.
Training Details 
Data Sources:
jondurbin/gutenberg-dpo-v0.1
Methodology:
Finetuned using an RTX 4090 using ORPO for 3 epochs.
Hardware Used:
RTX 4090
LLM NameGemma2 Gutenberg 9B
Repository 🤗https://huggingface.co/nbeerbower/gemma2-gutenberg-9B 
Base Model(s)  Gemma 2 9B It SPPO Iter3   UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
Model Size9b
Required VRAM18.6 GB
Updated2026-05-02
Maintainernbeerbower
Model Typegemma2
Model Files  4.9 GB: 1-of-4   5.0 GB: 2-of-4   5.0 GB: 3-of-4   3.7 GB: 4-of-4
Model ArchitectureGemma2ForCausalLM
Licensegemma
Context Length8192
Model Max Length8192
Transformers Version4.42.4
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than nbeerbower/gemma2-gutenberg-9B.

Rank the Gemma2 Gutenberg 9B 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 v20260328a