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Fbt Gemma 7B by Mr-Bhaskar

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  Arxiv:1910.09700   4bit   Autotrain compatible   Conversational   Endpoints compatible   Gemma   Pytorch   Quantized   Region:us   Sft   Sharded   Trl   Unsloth

Fbt Gemma 7B Benchmarks

ARC: 62.03 vs 96.7 (so35)-35.9%
HellaSwag: 80.23 vs 95.3 (gpt4)-15.8%
MMLU: 63.81 vs 88.3 (so35)-27.7%
TruthfulQA: 49.89 vs 59 (gpt4)-15.4%
WinoGrande: 78.37 vs 87.5 (gpt4)-10.4%
GSM8K: 30.17 vs 96.4 (so35)-68.7%
LLME Score: 0.22775
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Fbt Gemma 7B Parameters and Internals

LLM NameFbt Gemma 7B
Repository 🤗https://huggingface.co/Mr-Bhaskar/fbt-gemma-7b 
Model Size7b
Required VRAM17.1 GB
Updated2024-10-18
MaintainerMr-Bhaskar
Model Typegemma
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   5.0 GB: 3-of-4   2.1 GB: 4-of-4
Quantization Type4bit
Model ArchitectureGemmaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.40.2
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typefloat16
Fbt Gemma 7B (Mr-Bhaskar/fbt-gemma-7b)

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Note: green Score (e.g. "73.2") means that the model is better than Mr-Bhaskar/fbt-gemma-7b.

Rank the Fbt Gemma 7B 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 v2024072803
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