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  • AI free languages models – datasets for training and testing AI https://pikabu.ru/story/memyi_kartinki_s_tekstom_12583677 New datasets for foreign languages ​​are constantly being added. These language models are not found in other datasets. For final adjustments.

    Language Model
  • Language Technology Partner Program. Memes (pictures with text) are quite complex models for training AI and AGI. It is necessary to accurately recognize the meaning of the text. For memes, these are usually jokes, humor, trolling using wordplay, a small amount of text for analysis, and the use of local concepts. In addition, it is necessary to correctly evaluate the picture – objects, the location of objects, their interaction, and the degree of correspondence between the picture and the text.
    https://agimodels.mywebforum.com/forum/discussion
    https://i.postimg.cc/3wMJpZ0J/AGI-training2.jpg
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    Based on UCI Machine Learning Repository
    Gain an edge with cutting-edge language models.
    http://pub39.bravenet.com/forum/3340891031/
    Download https://ieee-dataport.org/documents/agi-language-training

    Training Model
  • Data set number 00034 for final training and testing of AGI https://zezlmx.staticfast.com/ Subject: emotions, humor, memes, jokes

    AGI Models
  • Special datasets for final training or testing of AGI naturalness https://agidatasetsfree.createaforum.com/ for foreign languages. Topics – emotions, humor, jokes, trolling and why it is important for Steganography. More than 2000 models. Structural diagrams can be compiled for models, datasets can be scaled.

    Steganography
  • A standard cross-entropy loss function can be applied to soft labels. Training (examples https://oflameron.imgbb.com/ ) by the maximum likelihood method with a softmax classifier and hard labels may never converge – softmax cannot predict a probability exactly equal to 0 or 1, so it will endlessly continue training larger and larger weights, making more and more extreme predictions.
    http://shmeleff.com Extensive experience in creating data sets for final tuning of neural networks.

    Learning Process

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