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Write With Transformer, Hacker News

Write With Transformer, Hacker News


This web app, built by the Hugging Face team, is the official demo of thepytorch-transformersrepository’s text generation capabilities.

Checkpoints

🤓 Arxiv-NLP

Built on the OpenAI GPT-2 model, the Hugging Face team has fine-tuned the small version on a tiny dataset (60 MB of text) of Arxiv papers. The targeted subject is Natural Language Processing, resulting in a very Linguistics / Deep Learning oriented generation.

Models

🦄 GPT-2

The almighty king of text generation, GPT-2 comes in four available sizes, only three of which have been publicly made available. Feared for its fake news generation capabilities, it currently stands as the most syntactically coherent model. A direct successor to the original GPT, it reinforces the already established pre-training / fine-tuning killer duo. From the paper: Language Models are Unsupervised Multitask Learners by Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei and Ilya Sutskever.

💯 XLNet

Overcoming the unidirectional limit while maintaining an independent masking algorithm based on permutation, XLNet improves upon the state-of-the-art autoregressive model that is TransformerXL. Using a bidirectional context while keeping its autoregressive approach, this model outperforms BERT on 20 tasks while keeping an impressive generative coherence. From the paper: XLNet: Generalized Autoregressive Pretraining for Language Understanding, by Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov and Quoc V. Le.

☠️ GPT

Released by OpenAI, this architecture has shown that large gains on several NLP tasks can be achieved by generative pre-training a language model on unlabeled text before fine-tuning it on a downstream task. From the paper: Improving Language Understanding by Generative Pre-Training, by Alec Radford, Karthik Naraimhan, Tim Salimans and Ilya Sutskever.

Do you want to contribute or suggest a new model checkpoint? Open an issue onpytorch-transformers🔥.

“It is to write what calculators are to calculus.”

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