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  2. BLOOM (language model) - Wikipedia

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

    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]

  3. LangChain - Wikipedia

    en.wikipedia.org/wiki/LangChain

    LangChain is a software framework that helps facilitate the integration of large language models (LLMs) into applications. As a language model integration framework, LangChain's use-cases largely overlap with those of language models in general, including document analysis and summarization , chatbots , and code analysis .

  4. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    huggingface.co Hugging Face is a French-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.

  5. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.

  6. 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.

  7. Contrastive Language-Image Pre-training - Wikipedia

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

    Contrastive Language-Image Pre-training (CLIP) is a technique for training a pair of neural network models, one for image understanding and one for text understanding, using a contrastive objective. [1]

  8. PDF - Wikipedia

    en.wikipedia.org/wiki/PDF

    The imaging model of the Quartz graphics layer is based on the model common to Display PostScript and PDF, leading to the nickname Display PDF. The Preview application can display PDF files, as can version 2.0 and later of the Safari web browser. System-level support for PDF allows macOS applications to create PDF documents automatically ...

  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.