Susant-Achary/distilgpt2-finetuned-constitution-of-india

Model Card for DistilGPT2 Fine-Tuned on the Indian Constitution

Model Summary

This is a fine-tuned version of DistilGPT2 on the Indian Constitution. It has been trained to generate text consistent with the style and language of the Indian Constitution, making it a useful resource for legal text generation and educational purposes.

Model Details

Model Description

This model is a fine-tuned version of the DistilGPT2 model, specifically trained on the text of the Indian Constitution. It can generate contextually accurate legal text and provides a demonstration of fine-tuning GPT-style models for domain-specific tasks.

• —Developed by: Susant Achary
• —Financed by: [No specific funding; self-driven project]
• —Shared by: Susant Achary
• —Model type: Causal Language Model (AutoRegressive Transformer)
• —Language(s) (NLP): English
• —License: Apache 2.0
• —Fine-tuned from: distilbert/distilgpt2

Model Sources

• —Repository: Susant Achary's Hugging Face
• —Demo: Use directly via Hugging Face Hub

Data Source Trained on

• —Resository:[Susant-Achary/constitution-of-india-dataset] ---

Uses

Direct Use

The model is suitable for generating:

• —Contextually accurate text resembling the Indian Constitution.
• —Legal or constitutional examples for research or education.
• —Domain-specific text generation tasks.

Downstream Use

The model can be further fine-tuned for:

• —Other legal text corpora.
• —Domain-specific legal or policy text generation.

Out-of-Scope Use

• —Malicious or unethical use, including generating misleading or harmful legal text.
• —Tasks requiring understanding or reasoning outside the scope of its training data (e.g., non-legal content).

Bias, Risks, and Limitations

Biases

• —The model is limited to the specific style and content of the Indian Constitution, which may not generalize well to other legal systems or contexts.

Limitations

• —Limited vocabulary: It was trained solely on the Indian Constitution, so it may struggle with prompts outside this domain.
• —Lacks reasoning: The model cannot provide explanations or legal reasoning.

Recommendations

• —Use responsibly in legal and educational contexts.
• —Verify generated text before usage to avoid inaccuracies or misinterpretations.

How to Get Started with the Model

Use the code below to get started with the model:

from transformers import pipeline

model_name = "Susant-Achary/distilgpt2-constitution-of-india"

gen_pipeline = pipeline(
    "text-generation",
    model=model_name, 
    tokenizer=model_name
)

prompt = "We, the people of India"
output = gen_pipeline(
    prompt,
    max_length=100,
    do_sample=True,
    temperature=0.8,
    top_k=100,
    top_p=0.95,
    num_return_sequences=1
)

print(output[0]['generated_text'])