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CLIP: https://openai.com/research/clip

They use a small text encoder and suggest that the simpler the model the better. Is there any reason why that is? Has anyone tried using a pretrained LLM as the text encoder and then fine tuning? I would assume the LLM would learn a lot better representation of the meaning of the text.

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