Fix architectures count
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Lysandre Debut
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@@ -39,7 +39,7 @@ State-of-the-art NLP for everyone
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Lower compute costs, smaller carbon footprint
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Lower compute costs, smaller carbon footprint
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- Researchers can share trained models instead of always retraining
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- Researchers can share trained models instead of always retraining
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- Practitioners can reduce compute time and production costs
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- Practitioners can reduce compute time and production costs
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- 8 architectures with over 30 pretrained models, some in more than 100 languages
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- 10 architectures with over 30 pretrained models, some in more than 100 languages
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Choose the right framework for every part of a model's lifetime
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Choose the right framework for every part of a model's lifetime
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- Train state-of-the-art models in 3 lines of code
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- Train state-of-the-art models in 3 lines of code
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@@ -111,7 +111,7 @@ At some point in the future, you'll be able to seamlessly move from pre-training
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## Model architectures
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## Model architectures
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🤗 Transformers currently provides 8 NLU/NLG architectures:
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🤗 Transformers currently provides 10 NLU/NLG architectures:
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1. **[BERT](https://github.com/google-research/bert)** (from Google) released with the paper [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://arxiv.org/abs/1810.04805) by Jacob Devlin, Ming-Wei Chang, Kenton Lee and Kristina Toutanova.
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1. **[BERT](https://github.com/google-research/bert)** (from Google) released with the paper [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://arxiv.org/abs/1810.04805) by Jacob Devlin, Ming-Wei Chang, Kenton Lee and Kristina Toutanova.
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2. **[GPT](https://github.com/openai/finetune-transformer-lm)** (from OpenAI) released with the paper [Improving Language Understanding by Generative Pre-Training](https://blog.openai.com/language-unsupervised/) by Alec Radford, Karthik Narasimhan, Tim Salimans and Ilya Sutskever.
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2. **[GPT](https://github.com/openai/finetune-transformer-lm)** (from OpenAI) released with the paper [Improving Language Understanding by Generative Pre-Training](https://blog.openai.com/language-unsupervised/) by Alec Radford, Karthik Narasimhan, Tim Salimans and Ilya Sutskever.
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