I’m trying to find a minimalistic RoBERTa example that I can modify and use for some research on protein folding.
So far all I can find is fairseq:

  
      github.com
  
  
    pytorch/fairseq/blob/master/examples/roberta/README.md 3
# RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://arxiv.org/abs/1907.11692

## Introduction

RoBERTa iterates on BERT's pretraining procedure, including training the model longer, with bigger batches over more data; removing the next sentence prediction objective; training on longer sequences; and dynamically changing the masking pattern applied to the training data. See the associated paper for more details.

### What's New:

- December 2020: German model (GottBERT) is available: [GottBERT](https://github.com/pytorch/fairseq/tree/master/examples/gottbert).
- January 2020: Italian model (UmBERTo) is available from Musixmatch Research: [UmBERTo](https://github.com/musixmatchresearch/umberto).
- November 2019: French model (CamemBERT) is available: [CamemBERT](https://github.com/pytorch/fairseq/tree/master/examples/camembert).
- November 2019: Multilingual encoder (XLM-RoBERTa) is available: [XLM-R](https://github.com/pytorch/fairseq/tree/master/examples/xlmr).
- September 2019: TensorFlow and TPU support via the [transformers library](https://github.com/huggingface/transformers).
- August 2019: RoBERTa is now supported in the [pytorch-transformers library](https://github.com/huggingface/pytorch-transformers).
- August 2019: Added [tutorial for finetuning on WinoGrande](https://github.com/pytorch/fairseq/tree/master/examples/roberta/wsc#roberta-training-on-winogrande-dataset).
- August 2019: Added [tutorial for pretraining RoBERTa using your own data](README.pretraining.md).

## Pre-trained models


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Which definitely have the model I’m looking for, but it also looks like there is tons of other stuff that makes just extracting the model quite complicated.
Does anyone have or knows of a simpler place to get a base RoBERTa model, it shouldn’t be pretrained at all, I just want the base framework.