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The Transformers library is a Python package that contains open-source implementations of transformer models for text, image, and audio tasks. It is compatible with the PyTorch , TensorFlow and JAX deep learning libraries and includes implementations of notable models like BERT and GPT-2 . [ 17 ]
[[Category:Programming language templates]] to the <includeonly> section at the bottom of that page. Otherwise, add <noinclude>[[Category:Programming language templates]]</noinclude> to the end of the template code, making sure it starts on the same line as the code's last character.
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [ 1 ] [ 2 ] Like the original Transformer model, [ 3 ] T5 models are encoder-decoder Transformers , where the encoder processes the input text, and the decoder generates the output text.
The use of templates as a metaprogramming technique requires two distinct operations: a template must be defined, and a defined template must be instantiated.The generic form of the generated source code is described in the template definition, and when the template is instantiated, the generic form in the template is used to generate a specific set of source code.
All transformers have the same primary components: Tokenizers, which convert text into tokens. Embedding layer, which converts tokens and positions of the tokens into vector representations. Transformer layers, which carry out repeated transformations on the vector representations, extracting more and more linguistic information.
To change this template's initial visibility, the |state= parameter may be used: {{Transformers | state = collapsed}} will show the template collapsed, i.e. hidden apart from its title bar. {{Transformers | state = expanded}} will show the template expanded, i.e. fully visible.
GPT-J or GPT-J-6B is an open-source large language model (LLM) developed by EleutherAI in 2021. [1] As the name suggests, it is a generative pre-trained transformer model designed to produce human-like text that continues from a prompt.
Code Llama is a fine-tune of LLaMa 2 with code specific datasets. 7B, 13B, and 34B versions were released on August 24, 2023, with the 70B releasing on the January 29, 2024. [29] Starting with the foundation models from LLaMa 2, Meta AI would train an additional 500B tokens of code datasets, before an additional 20B token of long-context data ...