front/views/landing.hbs

<header>
	<img class="logo" src="/front/assets/unicorn-tweaked.svg">
	<div class="title">
		Write With Transformer
	</div>
	<div class="tagline">
		Get a modern neural network to<br>auto-complete your thoughts.
	</div>
</header>

<div class="section-models">
	<div class="container">
		<div class="description">
			This web app, built by the Hugging Face team, is the official demo of the 
			<a href="https://github.com/huggingface/transformers"><code>🤗/transformers</code></a>
			repository's text generation capabilities.
		</div>
		<div class="github-repo">
			<a 
				class="github-button"
				href="https://github.com/huggingface/transformers" data-size="large" data-show-count="true" aria-label="Star huggingface/transformers on GitHub">
				Star
			</a>
		</div>
		
		<div class="title-section">Models</div>
		
		<div class="model" data-tilt>
			<div class="model-title">🦄 GPT-2</div>
			<div class="model-details">
				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.
			</div>
			<div class="model-bottom">
				<a class="btn btn-primary" href="/doc/gpt2-large">Start writing</a>
			</div>
		</div>
		
		<div class="model" data-tilt>
			<div class="model-title">💯 XLNet</div>
			<div class="model-details">
				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.
			</div>
			<div class="model-bottom">
				<a class="btn btn-primary" href="/doc/xlnet">Start writing</a>
			</div>
		</div>
		
		<div class="model" data-tilt>
			<div class="model-title">☠️ GPT</div>
			<div class="model-details">
				Released by OpenAI, this seminal 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.
			</div>
			<div class="model-bottom">
				<a class="btn btn-primary" href="/doc/gpt">Start writing</a>
			</div>
		</div>
		
		<a href="/model/distil-gpt2">
			<div class="model" data-tilt>
				<div class="model-title">🐎 DistilGPT-2</div>
				<div class="model-details">
					The student of the now ubiquitous GPT-2 does not come short of its teacher’s expectations. 
					Obtained by distillation, DistilGPT-2 weighs 37% less, and is twice as fast as its OpenAI counterpart, while keeping the same generative power. 
					Runs smoothly on an iPhone 7. The dawn of lightweight generative <br>transformers?
				</div>
				<div class="model-bottom">
					<a class="btn btn-details" href="/model/distil-gpt2">More info</a>
					<a class="btn btn-primary" href="/doc/distil-gpt2">Start writing</a>
				</div>
			</div>
		</a>
		
		<a href="/model/arxiv-nlp">
			<div class="model" data-tilt>
				<div class="model-title">🤓 Arxiv-NLP</div>
				<div class="model-details">
					Built on the OpenAI GPT-2 model, the Hugging Face team has fine-tuned the small version on a tiny dataset (60MB of text) of Arxiv papers. 
					The targeted subject is Natural Language Processing, resulting in a very Linguistics/Deep Learning oriented generation.
				</div>
				<div class="model-bottom">
					<a class="btn btn-details" href="/model/arxiv-nlp">More info</a>
					<a class="btn btn-primary" href="/doc/arxiv-nlp">Start writing</a>
				</div>
			</div>
		</a>
		
		<div class="description">
			Do you want to contribute or suggest a new model checkpoint? Open an issue on
			<a href="https://github.com/huggingface/transformers"><code>🤗/transformers</code></a> 🔥.
		</div>
		<div class="quote">
			“It is to writing what calculators are to calculus.”
		</div>
	</div>
</div>

<div class="section-footer">
	<div class="container">
		<div class="title">
			Latest featured public documents
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		<ul class="documents">
			{{#each docs}}
				<li>
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