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// An object with different embedding types. The length of each embedding type array will be the same as the length of the original `texts` array.typeEmbedByTypeResponseEmbeddingsstruct {
// An array of float embeddings.Float [][]float64`json:"float,omitempty" url:"float,omitempty"`// An array of signed int8 embeddings. Each value is between -128 and 127.Int8 [][]float64`json:"int8,omitempty" url:"int8,omitempty"`// An array of unsigned int8 embeddings. Each value is between 0 and 255.Uint8 [][]float64`json:"uint8,omitempty" url:"uint8,omitempty"`// An array of packed signed binary embeddings. The length of each binary embedding is 1/8 the length of the float embeddings of the provided model. Each value is between -128 and 127.Binary [][]float64`json:"binary,omitempty" url:"binary,omitempty"`// An array of packed unsigned binary embeddings. The length of each binary embedding is 1/8 the length of the float embeddings of the provided model. Each value is between 0 and 255.Ubinary [][]float64`json:"ubinary,omitempty" url:"ubinary,omitempty"`_rawJSON json.RawMessage
}
The text was updated successfully, but these errors were encountered:
Hey @Dmarcotrigiano thanks for pointing this out. Unfortunately we currently generate the library and aren't able to narrow these types. The values should still be correct if you want to cast them to the correct type. I will investigate improving this situation. Let me know if you have any more issues with usage.
The type in question:
The text was updated successfully, but these errors were encountered: