From 6ba254ee5477c242668aac458c6d4539931bc7c0 Mon Sep 17 00:00:00 2001 From: Clement Date: Thu, 23 Apr 2020 14:19:45 -0400 Subject: [PATCH] quick fix wording readme for community models (#3900) --- README.md | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index b2c8cafdab..0faacb914e 100644 --- a/README.md +++ b/README.md @@ -22,14 +22,11 @@

State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch -🤗 Transformers (formerly known as `pytorch-transformers` and `pytorch-pretrained-bert`) provides state-of-the-art general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet, CTRL...) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch. +🤗 Transformers (formerly known as `pytorch-transformers` and `pytorch-pretrained-bert`) provides state-of-the-art general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet, T5, CTRL...) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over thousands of pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch. [![](https://sourcerer.io/fame/clmnt/huggingface/transformers/images/0)](https://sourcerer.io/fame/clmnt/huggingface/transformers/links/0)[![](https://sourcerer.io/fame/clmnt/huggingface/transformers/images/1)](https://sourcerer.io/fame/clmnt/huggingface/transformers/links/1)[![](https://sourcerer.io/fame/clmnt/huggingface/transformers/images/2)](https://sourcerer.io/fame/clmnt/huggingface/transformers/links/2)[![](https://sourcerer.io/fame/clmnt/huggingface/transformers/images/3)](https://sourcerer.io/fame/clmnt/huggingface/transformers/links/3)[![](https://sourcerer.io/fame/clmnt/huggingface/transformers/images/4)](https://sourcerer.io/fame/clmnt/huggingface/transformers/links/4)[![](https://sourcerer.io/fame/clmnt/huggingface/transformers/images/5)](https://sourcerer.io/fame/clmnt/huggingface/transformers/links/5)[![](https://sourcerer.io/fame/clmnt/huggingface/transformers/images/6)](https://sourcerer.io/fame/clmnt/huggingface/transformers/links/6)[![](https://sourcerer.io/fame/clmnt/huggingface/transformers/images/7)](https://sourcerer.io/fame/clmnt/huggingface/transformers/links/7) ### Features - -- As easy to use as pytorch-transformers -- As powerful and concise as Keras - High performance on NLU and NLG tasks - Low barrier to entry for educators and practitioners @@ -41,7 +38,7 @@ State-of-the-art NLP for everyone Lower compute costs, smaller carbon footprint - Researchers can share trained models instead of always retraining - Practitioners can reduce compute time and production costs -- 10 architectures with over 30 pretrained models, some in more than 100 languages +- Dozens of architectures with over 1,000 pretrained models, some in more than 100 languages Choose the right framework for every part of a model's lifetime - Train state-of-the-art models in 3 lines of code