 How to use Best way to use is to finetune on your own task, but you can also extract features directly. To get the features of a given text in PyTorch:  ```python from transformers import RobertaTokenizer, RobertaModel tokenizer = RobertaTokenizer.from_pretrained('ibm/ColD-Fusion') model = RobertaModel.from_pretrained('ibm/ColD-Fusion') text = "Replace me by any text you'd like." encoded_input = tokenizer(text, return_tensors='pt') output = model(**encoded_input) ```  and in TensorFlow:  ```python from transformers import RobertaTokenizer, TFRobertaModel tokenizer = RobertaTokenizer.from_pretrained('ibm/ColD-Fusion') model = TFRobertaModel.from_pretrained('ibm/ColD-Fusion') text = "Replace me by any text you'd like." encoded_input = tokenizer(text, return_tensors='tf') output = model(encoded_input) ```  