andrewkroening
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---
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language: en
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tags:
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- conversational
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license: cc
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---
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# GPT-2
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This model is based on a GPT-2 model which was fine-tuned on a Hugging Face dataset. It is intended largely as an illustrative example and is not intended to be used for any serious purpose. It's trained on a movie script for goodness' sake.
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Disclaimer: The team releasing GPT-2 also wrote a
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[model card](https://github.com/openai/gpt-2/blob/master/model_card.md) for their model. Content from this model card
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has been written by the Hugging Face team to complete the information they provided and give specific examples of bias.
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## Acknowledgements
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There are several sources of inspiration and insight for the project that spawned this model. I'd like to recognize them up front:
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* The [Microsoft DialoGPT-Medium](https://huggingface.co/microsoft/DialoGPT-medium?text=Hi.) model page was very insightful for getting stated.
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* Lynn Zheng [r3dhummingbird](https://huggingface.co/r3dhummingbird/DialoGPT-medium-joshua?text=Hey+my+name+is+Thomas%21+How+are+you%3F) put together one heck of an awesome tutorial on how to fine-tune GPT-2 for conversational purposes. I used her tutorial as a starting point for this project. Check out the [Github repo here.](https://github.com/RuolinZheng08/twewy-discord-chatbot)
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* [This article](https://towardsdatascience.com/make-your-own-rick-sanchez-bot-with-transformers-and-dialogpt-fine-tuning-f85e6d1f4e30) was also very insightful. Written by Rostyslav Neskorozhenyi.
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* From a lineage standpoint, it looks like Nathan Cooper kicked this whole thing off with this [notebook.](https://github.com/ncoop57/i-am-a-nerd/blob/master/_notebooks/2020-05-12-chatbot-part-1.ipynb)
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* Noah Gift figured out a few of the big pieces in [this repository.](https://github.com/nogibjj/hugging-face-tutorial-practice)
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* I'd be remiss if I also didn't mention Hugging Face's own support [documentation](https://huggingface.co/transformers/v2.0.0/examples.html#gpt-2-gpt-and-causal-language-modeling) and team. All around great.
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## Model description
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This model uses GPT-2 Medium as a base model and was fine-tuned using scripts from the original (and best) Star Wars Trilogy. In this particular case, it was fine-tuned on Lord Vader's 140-some lines. This is not a lot, and thus the model should not be assumed to have serious integrity. It's just a fun little project.
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## Intended uses & limitations
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This model is intended to be used for fun and entertainment. Don't take it too seriously.
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### Ways to use
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You can always chat with the model directly on the Hugging Face website. Just click the "Chat" button on the right side of the model page.
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If you want to use the model in your own project, I recommend you train it better using much more data.
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To access the GitHub repository I used to train this model, click [here](https://github.com/nogibjj/hugging-face-gpt-trainer/tree/gpt-fine-tune)
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## Fine-tuning data
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The script to generate this model takes a Hugging Face data set in this approximate format:
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| Speaker | Text |
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| --- | --- |
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| Luke | Hello there. |
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| Han | General Kenobi. |
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| Luke | You are a bold one. |
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The script then asks the user to define parameters for making the dataset and proceeding to fine-tuning. The actual dataset for this model can be found [here.](andrewkroening/Star-wars-scripts-dialogue-IV-VI)
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