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  2. Contrastive Language-Image Pre-training - Wikipedia

    en.wikipedia.org/wiki/Contrastive_Language-Image...

    In the original OpenAI CLIP report, they reported training 5 ResNet and 3 ViT (ViT-B/32, ViT-B/16, ViT-L/14). Each was trained for 32 epochs. The largest ResNet model took 18 days to train on 592 V100 GPUs. The largest ViT model took 12 days on 256 V100 GPUs. All ViT models were trained on 224x224 image resolution.

  3. Vision transformer - Wikipedia

    en.wikipedia.org/wiki/Vision_transformer

    A vision transformer (ViT) is a transformer designed for computer vision. [1] A ViT decomposes an input image into a series of patches (rather than text into tokens ), serializes each patch into a vector, and maps it to a smaller dimension with a single matrix multiplication .

  4. What is your body shape and what does it say about your ... - AOL

    www.aol.com/body-shape-does-health-081758284.html

    The body-positive movement has encouraged people, especially women, to see beauty in all shapes and sizes, and it's reminded us that body ideals are culturally constructed and not based on science.

  5. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    huggingface.co Hugging Face, Inc. is an American company that develops computation tools for building applications using machine learning . It is known for its transformers library built for natural language processing applications.

  6. DALL-E - Wikipedia

    en.wikipedia.org/wiki/DALL-E

    DALL-E was developed and announced to the public in conjunction with CLIP (Contrastive Language-Image Pre-training). [23] CLIP is a separate model based on contrastive learning that was trained on 400 million pairs of images with text captions scraped from the Internet. Its role is to "understand and rank" DALL-E's output by predicting which ...

  7. BLOOM (language model) - Wikipedia

    en.wikipedia.org/wiki/BLOOM_(language_model)

    BigScience was led by HuggingFace and involved several hundreds of researchers and engineers from France and abroad representing both the academia and the private sector. BigScience was supported by a large-scale public compute grant on the French public supercomputer Jean Zay, managed by GENCI and IDRIS , on which it was trained.

  8. T5 (language model) - Wikipedia

    en.wikipedia.org/wiki/T5_(language_model)

    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.

  9. Stable Diffusion - Wikipedia

    en.wikipedia.org/wiki/Stable_Diffusion

    Stable Diffusion is a deep learning, text-to-image model released in 2022 based on diffusion techniques. The generative artificial intelligence technology is the premier product of Stability AI and is considered to be a part of the ongoing artificial intelligence boom.