data encoders
mipangilio ya data
audio encoders
mipangilio ya audio
video encoders
mipangilio ya video
using encoders
kupitia mipangilio
encoder settings
mipangilio ya encoder
encoder output
ma出力 ya encoder
encoder algorithm
algorithmi ya encoder
encoder library
maudhulio ya encoder
encoder hardware
hardware ya encoder
encoder role
utulizi wa encoder
the audio encoder converted the speech into a numerical representation.
Mtumiaji wa maudhui umetumia mshahara wa maelezo ya maelezo kwa maelezo ya hisa.
we use video encoders to compress large video files for streaming.
Tutumia mshahara wa video kusimamia faili ya video makubwa kwa kusambaza.
the neural network employs encoders and decoders for sequence-to-sequence tasks.
Mshahara wa mshahara huyu unatumia mshahara na mshahara kwa mshahara kwa mshahara.
the image encoder extracted features from the input image.
Mshahara wa picha umekumbusha sifuri za picha ya input.
the data encoder transformed the raw data into a usable format.
Mshahara wa data umekumbusha data ya kusambaza kwa fomati inayotumia.
the hardware encoders efficiently compressed the video stream.
Mshahara wa hardware wamekumbusha video stream kwa mafanikio.
the language encoders learned to represent words and sentences.
Mshahara wa lugha wameamini kwa kujenga maneno na sentensi.
the system utilizes multiple encoders for different data types.
Majumla inatumia mshahara makubwa kwa mshahara maziki ya data.
the loss function penalizes errors in the encoder's output.
Fungu ya kutoweka inapunguza mshahara katika output ya mshahara.
the encoder’s architecture is crucial for model performance.
Mshahara wa mshahara ni muhimu kwa mafanikio ya model.
we are evaluating different encoders for optimal performance.
Tutafanya maelezo ya mshahara maziki kwa mafanikio ya mshahara.
data encoders
mipangilio ya data
audio encoders
mipangilio ya audio
video encoders
mipangilio ya video
using encoders
kupitia mipangilio
encoder settings
mipangilio ya encoder
encoder output
ma出力 ya encoder
encoder algorithm
algorithmi ya encoder
encoder library
maudhulio ya encoder
encoder hardware
hardware ya encoder
encoder role
utulizi wa encoder
the audio encoder converted the speech into a numerical representation.
Mtumiaji wa maudhui umetumia mshahara wa maelezo ya maelezo kwa maelezo ya hisa.
we use video encoders to compress large video files for streaming.
Tutumia mshahara wa video kusimamia faili ya video makubwa kwa kusambaza.
the neural network employs encoders and decoders for sequence-to-sequence tasks.
Mshahara wa mshahara huyu unatumia mshahara na mshahara kwa mshahara kwa mshahara.
the image encoder extracted features from the input image.
Mshahara wa picha umekumbusha sifuri za picha ya input.
the data encoder transformed the raw data into a usable format.
Mshahara wa data umekumbusha data ya kusambaza kwa fomati inayotumia.
the hardware encoders efficiently compressed the video stream.
Mshahara wa hardware wamekumbusha video stream kwa mafanikio.
the language encoders learned to represent words and sentences.
Mshahara wa lugha wameamini kwa kujenga maneno na sentensi.
the system utilizes multiple encoders for different data types.
Majumla inatumia mshahara makubwa kwa mshahara maziki ya data.
the loss function penalizes errors in the encoder's output.
Fungu ya kutoweka inapunguza mshahara katika output ya mshahara.
the encoder’s architecture is crucial for model performance.
Mshahara wa mshahara ni muhimu kwa mafanikio ya model.
we are evaluating different encoders for optimal performance.
Tutafanya maelezo ya mshahara maziki kwa mafanikio ya mshahara.
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