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Eu Ai Act Using Finetuned Gemma by Orcawise

 »  All LLMs  »  Orcawise  »  Eu Ai Act Using Finetuned Gemma   URL Share it on

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  4-bit   Adapter Base model:adapter:google/gemm...   Base model:google/gemma-2b   Bitsandbytes   Finetuned   Gemma   Generated from trainer   Lora   Peft   Region:us   Safetensors   Sft   Tensorboard   Trl
Model Card on HF 🤗: https://huggingface.co/Orcawise/eu_ai_act_using_finetuned_gemma 

Eu Ai Act Using Finetuned Gemma Benchmarks

LLME Score: 0.17916
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Eu Ai Act Using Finetuned Gemma (Orcawise/eu_ai_act_using_finetuned_gemma)

Eu Ai Act Using Finetuned Gemma Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
Legal Consultation, Compliance Strategy Development, Educational Tool
Primary Use Cases:
Assist legal professionals by providing answers to EU AI Act questions, Support compliance officers, Serve as an educational resource
Limitations:
Model should not be used as standalone legal advice, Understanding of the act can be further verified via official public documents
Considerations:
Questions should be framed relating to the EU AI Act
Additional Notes 
The model is based on the fine-tuning of the google/gemma-2b model specifically for the EU AI Act context.
Training Details 
Data Sources:
Questions and answers on the EU AI Act
Data Volume:
1023 questions and answer pairs
Input Output 
Input Format:
Input a question related to the EU AI Act
Output Format:
Response reflecting current understanding of the EU AI Act's provisions
Performance Tips:
Questions should be specific and related to the EU AI Act.
LLM NameEu Ai Act Using Finetuned Gemma
Repository 🤗https://huggingface.co/Orcawise/eu_ai_act_using_finetuned_gemma 
Base Model(s)  Gemma 2B   google/gemma-2b
Model Size2b
Required VRAM0 GB
Updated2025-02-22
MaintainerOrcawise
Model Files  0.0 GB   0.0 GB
Model ArchitectureAdapter
Licensegemma
Is Biasednone
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesq_proj|v_proj
LoRA Alpha8
LoRA Dropout0
R Param4

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Note: green Score (e.g. "73.2") means that the model is better than Orcawise/eu_ai_act_using_finetuned_gemma.

Rank the Eu Ai Act Using Finetuned Gemma 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 v20241227
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