---
library_name: transformers
tags:
- text-generation
- causal-lm
- gpt2
- trump
---

# Model Card for `cjerzak/trump-speeches-gpt2-finetune`

This is a fine-tuned version of the GPT-2 language model on a collection of 10 Donald Trump speeches. The original speeches are available at [ryanmcdermott/trump-speeches](https://github.com/ryanmcdermott/trump-speeches). This model is intended for experimentation with text generation and for demonstration/educational purposes.

---

## Model Details

### Model Description

- **Developed by:** Fine-tuning OpenAI's original GPT-2.
- **Model type:** Causal Language Model (GPT-2).
- **Language(s) (NLP):** English.
- **License:** [GPT-2’s license](https://huggingface.co/gpt2) (MIT-based). The fine-tuning code is also available and may be under a different open-source license; consult the repository for details.
- **Finetuned from model:** [`gpt2`](https://huggingface.co/gpt2).
- **Shared by:** [cjerzak on Hugging Face](https://huggingface.co/cjerzak).

Because it was fine-tuned on a small set of speeches, the model has learned stylistic patterns, phrases, and vocabulary frequently used in Donald Trump’s rhetoric. **Note**: This model is primarily for demonstration and to illustrate the use of GPT-2 fine-tuning. It should not be considered a comprehensive or robust representation of all of Donald Trump’s speeches.

### Model Sources

- **Repository:** [cjerzak/trump-speeches-gpt2-finetune on Hugging Face](https://huggingface.co/cjerzak/trump-speeches-gpt2-finetune)
- **Training Data Source:** [ryanmcdermott/trump-speeches](https://github.com/ryanmcdermott/trump-speeches)

---

## Uses

### Direct Use

- **Text Generation / Experimentation**: You can use this model to generate text in a style that somewhat mimics Donald Trump's speeches. It is well-suited as a teaching or demonstration model for fine-tuning GPT-2.

### Downstream Use

- **Creative Projects / Educational Examples**: If you want to incorporate a “Trump-like” text generation style in creative applications or show how GPT-2 behaves when fine-tuned on a small, domain-specific dataset.

---

## Bias, Risks, and Limitations

Because the training data consists of Donald Trump's speeches, the model may exhibit:
- **Stylistic Bias**: The model might produce text with repetitive rhetorical patterns or phrases.
- **Political Bias / Offensiveness**: The original speeches may contain language or statements that some users find offensive or controversial.
- **Limited Generalization**: With only 10 speeches, the model’s language patterns are narrowly focused. It may produce text with limited variety or slightly nonsensical completions outside of the style/subject matter present in the training data.

### Recommendations

- **Content Filtering**: If deploying publicly, consider adding filters or moderation layers to avoid offensive content.
- **Awareness**: Users should be aware of potential biases in the generated text. Given the small dataset, it can amplify certain topics or phrasings.
- **Educational Use**: Primarily recommended for demonstration or educational projects, not as a production-level model.

---

## How to Get Started with the Model

Install the necessary packages:
```bash
pip install transformers accelerate torch