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---
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language: en
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license: mit
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---
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# GPT-Neo 2.7B - Janeway
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## Model Description
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GPT-Neo 2.7B-Janeway is a finetune created using EleutherAI's GPT-Neo 2.7B model.
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## Training data
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The training data contains around 2210 ebooks, mostly in the sci-fi and fantasy genres. The dataset is based on the same dataset used by GPT-Neo-2.7B-Picard, with 20% more data in various genres.
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Some parts of the dataset have been prepended using the following text: `[Genre: <genre1>,<genre2>]`
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### How to use
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You can use this model directly with a pipeline for text generation. This example generates a different sequence each time it's run:
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```py
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>>> from transformers import pipeline
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>>> generator = pipeline('text-generation', model='KoboldAI/GPT-Neo-2.7B-Janeway')
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>>> generator("Welcome Captain Janeway, I apologize for the delay.", do_sample=True, min_length=50)
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[{'generated_text': 'Welcome Captain Janeway, I apologize for the delay."\nIt's all right," Janeway said. "I'm certain that you're doing your best to keep me informed of what\'s going on."'}]
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```
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### Limitations and Biases
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GPT-Neo was trained as an autoregressive language model. This means that its core functionality is taking a string of text and predicting the next token. While language models are widely used for tasks other than this, there are a lot of unknowns with this work.
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GPT-Neo was trained on the Pile, a dataset known to contain profanity, lewd, and otherwise abrasive language. Depending on your usecase GPT-Neo may produce socially unacceptable text. See Sections 5 and 6 of the Pile paper for a more detailed analysis of the biases in the Pile.
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As with all language models, it is hard to predict in advance how GPT-Neo will respond to particular prompts and offensive content may occur without warning. We recommend having a human curate or filter the outputs before releasing them, both to censor undesirable content and to improve the quality of the results.
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### BibTeX entry and citation info
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The model is made using the following software:
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```bibtex
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@software{gpt-neo,
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author = {Black, Sid and
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Leo, Gao and
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Wang, Phil and
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Leahy, Connor and
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Biderman, Stella},
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title = {{GPT-Neo: Large Scale Autoregressive Language
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Modeling with Mesh-Tensorflow}},
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month = mar,
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year = 2021,
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note = {{If you use this software, please cite it using
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these metadata.}},
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publisher = {Zenodo},
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version = {1.0},
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doi = {10.5281/zenodo.5297715},
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url = {https://doi.org/10.5281/zenodo.5297715}
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}
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``` |
