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| The size of the generated images | You have to log in to add a translation. | Details | |
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| Size | You have to log in to add a translation. | Details | |
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| The number of images to generate | You have to log in to add a translation. | Details | |
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| Nubmer | You have to log in to add a translation. | Details | |
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| Settings for Image | You have to log in to add a translation. | Details | |
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| The model parameter refers to the specific version of the GPT-3 architecture that is being used. There are several different versions of the GPT-3 model available, each with different levels of complexity and computational power. | You have to log in to add a translation. | Details | |
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The model parameter refers to the specific version of the GPT-3 architecture that is being used. There are several different versions of the GPT-3 model available, each with different levels of complexity and computational power.
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| Models | You have to log in to add a translation. | Details | |
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| The best of parameter controls how many of the model's generated responses are returned to the user. For example, setting best of to 3 will result in the model generating 3 different responses, and returning the one that it deems to be the best. This can be used to increase the likelihood of getting a high-quality response from the model. | You have to log in to add a translation. | Details | |
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The best of parameter controls how many of the model's generated responses are returned to the user. For example, setting best of to 3 will result in the model generating 3 different responses, and returning the one that it deems to be the best. This can be used to increase the likelihood of getting a high-quality response from the model.
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| Best Of | You have to log in to add a translation. | Details | |
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| The frequency penalty parameter penalizes the model for repeating certain words or phrases in its response. This can be used to encourage the model to generate more varied and natural-sounding responses. | You have to log in to add a translation. | Details | |
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The frequency penalty parameter penalizes the model for repeating certain words or phrases in its response. This can be used to encourage the model to generate more varied and natural-sounding responses.
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| Frequency penalty | You have to log in to add a translation. | Details | |
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| The presence penalty parameter penalizes the model for using certain words or phrases in its response. This can be used to encourage the model to generate more diverse and original responses. | You have to log in to add a translation. | Details | |
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The presence penalty parameter penalizes the model for using certain words or phrases in its response. This can be used to encourage the model to generate more diverse and original responses.
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| Presence penalty | You have to log in to add a translation. | Details | |
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| The temperature parameter controls the randomness and creativity of the model's responses. A higher temperature will result in more unpredictable and diverse responses, while a lower temperature will produce more conservative and predictable responses. | You have to log in to add a translation. | Details | |
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The temperature parameter controls the randomness and creativity of the model's responses. A higher temperature will result in more unpredictable and diverse responses, while a lower temperature will produce more conservative and predictable responses.
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| Temperature | You have to log in to add a translation. | Details | |
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