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93 lines
3.0 KiB
ReStructuredText
93 lines
3.0 KiB
ReStructuredText
OpenAI GPT
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Overview
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~~~~~~~~~~~~~~~~~~~~~
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OpenAI GPT model was proposed in `Improving Language Understanding by Generative Pre-Training`_
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by Alec Radford, Karthik Narasimhan, Tim Salimans and Ilya Sutskever. It's a causal (unidirectional)
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transformer pre-trained using language modeling on a large corpus will long range dependencies, the Toronto Book Corpus.
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The abstract from the paper is the following:
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*Natural language understanding comprises a wide range of diverse tasks such
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as textual entailment, question answering, semantic similarity assessment, and
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document classification. Although large unlabeled text corpora are abundant,
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labeled data for learning these specific tasks is scarce, making it challenging for
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discriminatively trained models to perform adequately. We demonstrate that large
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gains on these tasks can be realized by generative pre-training of a language model
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on a diverse corpus of unlabeled text, followed by discriminative fine-tuning on each
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specific task. In contrast to previous approaches, we make use of task-aware input
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transformations during fine-tuning to achieve effective transfer while requiring
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minimal changes to the model architecture. We demonstrate the effectiveness of
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our approach on a wide range of benchmarks for natural language understanding.
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Our general task-agnostic model outperforms discriminatively trained models that
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use architectures specifically crafted for each task, significantly improving upon the
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state of the art in 9 out of the 12 tasks studied.*
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Tips:
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- GPT is a model with absolute position embeddings so it's usually advised to pad the inputs on
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the right rather than the left.
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- GPT was trained with a causal language modeling (CLM) objective and is therefore powerful at predicting the next
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token in a sequence. Leveraging this feature allows GPT-2 to generate syntactically coherent text as
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it can be observed in the `run_generation.py` example script.
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`Write With Transformer <https://transformer.huggingface.co/doc/gpt>`__ is a webapp created and hosted by
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Hugging Face showcasing the generative capabilities of several models. GPT is one of them.
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OpenAIGPTConfig
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~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.OpenAIGPTConfig
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:members:
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OpenAIGPTTokenizer
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~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.OpenAIGPTTokenizer
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:members:
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OpenAIGPTModel
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~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.OpenAIGPTModel
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:members:
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OpenAIGPTLMHeadModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.OpenAIGPTLMHeadModel
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:members:
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OpenAIGPTDoubleHeadsModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.OpenAIGPTDoubleHeadsModel
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:members:
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TFOpenAIGPTModel
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~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFOpenAIGPTModel
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:members:
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TFOpenAIGPTLMHeadModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFOpenAIGPTLMHeadModel
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:members:
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TFOpenAIGPTDoubleHeadsModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFOpenAIGPTDoubleHeadsModel
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:members:
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