readme: ---
  language: en
  license: openrail
  pipeline_tag: text-generation
  ---
  # GPT-Neo 1.3B - Muslim Traveler
  ## Model Description
  GPT-Neo 1.3B-Muslim Traveler is finetuned on EleutherAI's GPT-Neo 1.3B model.
  ## Training data
  The training data consists of travel texts written by ancient muslim travelers. See 'combined.txt' file in the model repository.
  ### How to use
  You can use this model directly with a pipeline for text generation. This example generates a different sequence each time it's run:
  ```py
  >>> from transformers import pipeline
  >>> generator = pipeline('text-generation', model='arputtick/GPT_Neo_muslim_travel')
  >>> generator("> You wake up.", do_sample=True, min_length=50)
  [{'generated_text': '> You wake up"\nYou get out of bed, don your armor and get out of the door in search for new adventures.'}]
  ```
  ### Limitations and Biases
  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.
  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.
  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. 
  ### BibTeX entry and citation info
  The model is made using the following software:
  ```bibtex
  @software{gpt-neo,
    author       = {Black, Sid and
                    Leo, Gao and
                    Wang, Phil and
                    Leahy, Connor and
                    Biderman, Stella},
    title        = {{GPT-Neo: Large Scale Autoregressive Language 
                     Modeling with Mesh-Tensorflow}},
    month        = mar,
    year         = 2021,
    note         = {{If you use this software, please cite it using 
                     these metadata.}},
    publisher    = {Zenodo},
    version      = {1.0},
    doi          = {10.5281/zenodo.5297715},
    url          = {https://doi.org/10.5281/zenodo.5297715}
  }
  ```