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language: |
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- en |
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pipeline_tag: text-generation |
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tags: |
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- science fiction |
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- text generation |
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--- |
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This model has been fine-tuned on the novels written by H G Wells. H G Wells is a famous author and is well known for his science fiction novels. He is known as the father of science fiction. |
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This model can be used to generate text in the style of H G Wells. Since this model has been trained on most novels of the science fiction genre by H G Wells, it produces text of the science fiction genre. |
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The limitations of this model are that it can only generate text in the style of H G Wells, and not in the style of any other author. It may also be prone to generate text that has the stereotypes that were present at that time. An ethical consideration that needs to be taken into account is that the generated text may have gender biases that were present at the time when H G Wells wrote these novels. |
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I created my own dataset to train this model. I chose 14 novels written by H G Wells for my dataset. Most of the novels in the dataset are of the genre science fiction. The dataset contains more than 1 million tokens. |
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The texts included in the corpus are novels written by H G Wells. The novels in the corpus are: |
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The Time Machine - 37677 |
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In the Days of the Comet - 95299 |
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The Food of the Gods - 90723 |
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Tales of Space and Time - 85850 |
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The World Set Free - 74971 |
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The War of the Worlds - 69530 |
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The First Men in the Moon - 81517 |
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The Invisible Man - 60581 |
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The Island of Doctor Moreau - 52073 |
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The Sleeper Awakes - 91274 |
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The War in the Air - 115573 |
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The Research Magnificient - 131866 |
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The Udying Fire - 52036 |
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The Red Room - 4618 |
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The total number of tokens in the corpus is 1043588 |