---

language:

• en license: apache-2.0 library_name: transformers pipeline_tag: text-generation tags:
• gpt2
• text-generation
• nlp
• deep-learning

---

GPT-2 Text Generation Model

Model Description

This project uses the GPT-2 Transformer architecture for natural language text generation.

The model generates meaningful text based on a given input prompt.

Model Details

• Model Name: GPT-2 Text Generation
• Developed by: Maryam033
• Model Architecture: GPT-2
• Model Type: Transformer-based Language Model
• Task: Text Generation
• Language: English
• Framework: Hugging Face Transformers

Intended Use

This model is designed for:

• Automatic text generation
• Text completion
• Natural language processing experiments
• Educational and research purposes

Model Architecture

GPT-2 is a decoder-only Transformer model that uses self-attention mechanisms to predict the next token in a sequence.

How to Use

from transformers import pipeline

generator = pipeline(
    "text-generation",
    model="Maryam033/gpt2-text-generation"
)

result = generator(
    "Artificial Intelligence is",
    max_length=50,
    num_return_sequences=1
)

print(result)

Training Information

• Base Model: GPT-2
• Training Framework: Hugging Face Transformers
• Training Method: Fine-tuning

Limitations

• Generated text may sometimes contain incorrect information.
• Output quality depends on training data.
• The model may generate repetitive text.

Author

Maryam Zubair Ahmed

Hugging Face: https://huggingface.co/Maryam033