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Concretely, one can construct an LLM that can understand images as follows: take a trained LLM, and take a trained image encoder . Make a small multilayered perceptron , so that for any image , the post-processed vector (()) has the same dimensions as an encoded token. That is an "image token".
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]
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Llama was trained on only publicly available information, and was trained at various model sizes, with the intention to make it more accessible to different hardware. The model was exclusively a foundation model , [ 6 ] although the paper contained examples of instruction fine-tuned versions of the model.
In March 2020, 15.ai, created by an anonymous MIT researcher, was a free web application that could generate convincing character voices using minimal training data. [42] The platform is credited as the first mainstream service to popularize AI voice cloning ( audio deepfakes ) in memes and content creation , influencing subsequent developments ...
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