karan842
/

IPC-gemma

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 library_name: transformers
-tags: []
 ---
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 ---
 library_name: transformers
+tags:
+- legal
+license: apache-2.0
+datasets:
+- karan842/ipc-sections
+metrics:
+- accuracy
 ---
 # Model Card for Model ID
 <!-- Provide a quick summary of what the model is/does. -->
 ### Model Description
+**IPC-Gemma: AI Model for Indian Legal Code Analysis**
+IPC-Gemma is an advanced AI model designed to assist with tasks related to the Indian Penal Code (IPC). Trained on a comprehensive dataset of IPC sections and legal case information, this model is capable of analyzing textual descriptions of illegal activities and providing relevant insights.
+Key features of IPC-Gemma:
+1. **IPC Section Lookup**: Given a description of an illegal act, the model can quickly identify the corresponding IPC section that covers that offense.
+2. **Offense and Punishment Prediction**: Based on the input description, IPC-Gemma can predict the specific offense committed and the associated punishment or penalty.
+3. **Interpretable Outputs**: Along with the predicted offense and punishment, the model provides the relevant IPC section details to offer transparency and context around its analysis.
+4. **Legal Domain Expertise**: Leveraging the Gemma language model architecture, IPC-Gemma has been fine-tuned to excel in understanding and reasoning about legal terminology and concepts.
+This model is particularly useful for legal professionals, law enforcement agencies, and individuals seeking to better understand the Indian legal system. By automating the process of identifying offenses and their corresponding punishments, IPC-Gemma can save time, improve accuracy, and enhance decision-making in a variety of legal and criminal justice applications.
+Whether you need to quickly look up the relevant IPC section for a given scenario or analyze the potential consequences of an illegal act, IPC-Gemma is a powerful AI tool that can provide valuable insights and support.
+- **Developed by:** Karan Shingde
+- **Language(s) (NLP):** English
+- **Finetuned from model:** google/gemma-2b-it
 ### Training Data
 <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+Training Data Link: https://huggingface.co/datasets/karan842/ipc-sections
 #### Hardware
+  Kaggle GPU-P100
 ## Model Card Authors [optional]
+Karan Shingde: karanshindgde@gmail.com