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Serialization & Deserialization for Requests

Hugging Face Inference Endpount comes with a default serving container which is used for all supported Transformers and Sentence-Transformers tasks and for custom inference handler. The serving container takes care of serialization and deserialization of the request and response payloads based on the content-type and accept headers of the request. That means that when you send a request with a JSON body and a content-type: application/json header, the serving container will deserialize the JSON payload into a Python dictionary and pass it to the inference handler and if you send a request with a accept: image/png header, the serving container will seralize the response from the task/custom handler into a image.

Below is a list of supported content-types and the deserialized payload that is passed to the inference handler.

Content-Type Payload
application/json dict
text/csv raw
text/plain raw
image/png binary
image/jpeg binary
image/jpg binary
image/tiff binary
image/bmp binary
image/gif binary
image/webp binary
image/x-image binary
audio/x-flac {"inputs": bytes(body)}
audio/flac {"inputs": bytes(body)}
audio/mpeg {"inputs": bytes(body)}
audio/x-mpeg-3 {"inputs": bytes(body)}
audio/wave {"inputs": bytes(body)}
audio/wav {"inputs": bytes(body)}
audio/x-wav {"inputs": bytes(body)}
audio/ogg {"inputs": bytes(body)}
audio/x-audio {"inputs": bytes(body)}
audio/webm {"inputs": bytes(body)}
audio/webm;codecs=opus {"inputs": bytes(body)}
audio/AMR {"inputs": bytes(body)}
audio/amr {"inputs": bytes(body)}
audio/AMR-WB {"inputs": bytes(body)}
audio/AMR-WB+ {"inputs": bytes(body)}
audio/m4a {"inputs": bytes(body)}
audio/x-m4a {"inputs": bytes(body)}

Below is a list of supported accept headers and the serialized payload is returned.

Accept Payload
application/json JSON
text/csv raw
text/plain raw
image/png binary
image/jpeg binary
image/jpg binary
image/tiff binary
image/bmp binary
image/gif binary
image/webp binary
image/x-image binary