CTRL ---------------------------------------------------- CTRL model was proposed in `CTRL: A Conditional Transformer Language Model for Controllable Generation `_ by Nitish Shirish Keskar*, Bryan McCann*, Lav R. Varshney, Caiming Xiong and Richard Socher. It's a causal (unidirectional) transformer pre-trained using language modeling on a very large corpus of ~140 GB of text data with the first token reserved as a control code (such as Links, Books, Wikipedia etc.). This model is a PyTorch `torch.nn.Module `_ sub-class. Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage and behavior. Note: if you fine-tune a CTRL model using the Salesforce code (https://github.com/salesforce/ctrl), you'll be able to convert from TF to our HuggingFace/Transformers format using the ``convert_tf_to_huggingface_pytorch.py`` script (see `issue #1654 `_). ``CTRLConfig`` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. autoclass:: transformers.CTRLConfig :members: ``CTRLTokenizer`` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. autoclass:: transformers.CTRLTokenizer :members: ``CTRLModel`` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. autoclass:: transformers.CTRLModel :members: ``CTRLLMHeadModel`` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. autoclass:: transformers.CTRLLMHeadModel :members: ``TFCTRLModel`` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. autoclass:: transformers.TFCTRLModel :members: ``TFCTRLLMHeadModel`` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. autoclass:: transformers.TFCTRLLMHeadModel :members: