|
--- |
|
language: en |
|
license: apache-2.0 |
|
--- |
|
|
|
# Roberta2Roberta_L-24_wikisplit EncoderDecoder model |
|
|
|
The model was introduced in |
|
[this paper](https://arxiv.org/abs/1907.12461) by Sascha Rothe, Shashi Narayan, Aliaksei Severyn and first released in [this repository](https://tfhub.dev/google/bertseq2seq/roberta24_cnndm/1). |
|
|
|
The model is an encoder-decoder model that was initialized on the `roberta-large` checkpoints for both the encoder |
|
and decoder and fine-tuned on sentence splitting on the [WikiSplit](https://github.com/google-research-datasets/wiki-split) dataset. |
|
|
|
Disclaimer: The model card has been written by the Hugging Face team. |
|
|
|
## How to use |
|
|
|
You can use this model for sentence splitting, *e.g.* |
|
|
|
**IMPORTANT**: The model was not trained on the `"` (double quotation mark) character -> so the before tokenizing the text, |
|
it is advised to replace all `"` (double quotation marks) with two single `'` (single quotation mark). |
|
|
|
```python |
|
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
|
|
|
tokenizer = AutoTokenizer.from_pretrained("google/roberta2roberta_L-24_wikisplit") |
|
model = AutoModelForSeq2SeqLM.from_pretrained("google/roberta2roberta_L-24_wikisplit") |
|
|
|
long_sentence = """Due to the hurricane, Lobsterfest has been canceled, making Bob very happy about it and he decides to open Bob 's Burgers for customers who were planning on going to Lobsterfest.""" |
|
|
|
input_ids = tokenizer(tokenizer.bos_token + long_sentence + tokenizer.eos_token, return_tensors="pt").input_ids |
|
output_ids = model.generate(input_ids)[0] |
|
print(tokenizer.decode(output_ids, skip_special_tokens=True)) |
|
# should output |
|
# Due to the hurricane, Lobsterfest has been canceled, making Bob very happy about it. He decides to open Bob's Burgers for customers who were planning on going to Lobsterfest. |
|
``` |
|
|
