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IPC Gemma by karan842

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  Autotrain compatible   Conversational   Dataset:karan842/ipc-sections   Endpoints compatible   Gemma   Legal   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/karan842/IPC-gemma 

IPC Gemma Benchmarks

LLME Score: 0.20143
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
IPC Gemma (karan842/IPC-gemma)

IPC Gemma Parameters and Internals

Model Type 
text analysis, legal code analysis
Use Cases 
Areas:
legal professionals, law enforcement agencies, individuals seeking understanding of Indian legal system
Applications:
legal code analysis, offense and punishment prediction, IPC section lookup
Primary Use Cases:
Offense and Punishment Prediction, IPC Section Lookup
Supported Languages 
English (NLP)
Training Details 
Data Sources:
karan842/ipc-sections
Hardware Used:
Kaggle GPU-P100
Model Architecture:
Gemma language model architecture
LLM NameIPC Gemma
Repository 🤗https://huggingface.co/karan842/IPC-gemma 
Model Size2b
Required VRAM5.1 GB
Updated2025-02-22
Maintainerkaran842
Model Typegemma
Model Files  5.0 GB: 1-of-2   0.1 GB: 2-of-2
Model ArchitectureGemmaForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.41.2
Tokenizer ClassGemmaTokenizer
Padding Token<eos>
Vocabulary Size256000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than karan842/IPC-gemma.

Rank the IPC Gemma 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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Release v20241227
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