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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 ]
BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [3]
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.
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.
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Photorealistic retinal images and vessel segmentations. Public domain. 2500 images with 1500*1152 pixels useful for segmentation and classification of veins and arteries on a single background. 2500 Images Classification, Segmentation 2020 [262] C. Valenti et al. EEG Database Study to examine EEG correlates of genetic predisposition to alcoholism.
Llama (Large Language Model Meta AI, formerly stylized as LLaMA) is a family of large language models (LLMs) released by Meta AI starting in February 2023. [2] [3] The latest version is Llama 3.3, released in December 2024.