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