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docs/source/en/model_doc/bertweet.mdx

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+<!--Copyright 2020 The HuggingFace Team. All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
+an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
+specific language governing permissions and limitations under the License.
+-->
+
+# BERTweet
+
+## Overview
+
+The BERTweet model was proposed in [BERTweet: A pre-trained language model for English Tweets](https://www.aclweb.org/anthology/2020.emnlp-demos.2.pdf) by Dat Quoc Nguyen, Thanh Vu, Anh Tuan Nguyen.
+
+The abstract from the paper is the following:
+
+*We present BERTweet, the first public large-scale pre-trained language model for English Tweets. Our BERTweet, having
+the same architecture as BERT-base (Devlin et al., 2019), is trained using the RoBERTa pre-training procedure (Liu et
+al., 2019). Experiments show that BERTweet outperforms strong baselines RoBERTa-base and XLM-R-base (Conneau et al.,
+2020), producing better performance results than the previous state-of-the-art models on three Tweet NLP tasks:
+Part-of-speech tagging, Named-entity recognition and text classification.*
+
+Example of use:
+
+```python
+>>> import torch
+>>> from transformers import AutoModel, AutoTokenizer
+
+>>> bertweet = AutoModel.from_pretrained("vinai/bertweet-base")
+
+>>> # For transformers v4.x+:
+>>> tokenizer = AutoTokenizer.from_pretrained("vinai/bertweet-base", use_fast=False)
+
+>>> # For transformers v3.x:
+>>> # tokenizer = AutoTokenizer.from_pretrained("vinai/bertweet-base")
+
+>>> # INPUT TWEET IS ALREADY NORMALIZED!
+>>> line = "SC has first two presumptive cases of coronavirus , DHEC confirms HTTPURL via @USER :cry:"
+
+>>> input_ids = torch.tensor([tokenizer.encode(line)])
+
+>>> with torch.no_grad():
+...     features = bertweet(input_ids)  # Models outputs are now tuples
+
+>>> # With TensorFlow 2.0+:
+>>> # from transformers import TFAutoModel
+>>> # bertweet = TFAutoModel.from_pretrained("vinai/bertweet-base")
+```
+
+This model was contributed by [dqnguyen](https://huggingface.co/dqnguyen). The original code can be found [here](https://github.com/VinAIResearch/BERTweet).
+
+## BertweetTokenizer
+
+[[autodoc]] BertweetTokenizer