Description
Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.asr_whisper_small_swedish_test_3000
is a Swedish model originally trained by ZinebSN.
This model is only compatible with PySpark 3.4 and above
How to use
audioAssembler = AudioAssembler() \
.setInputCol("audio_content") \
.setOutputCol("audio_assembler")
speechToText = WhisperForCTC.pretrained("asr_whisper_small_swedish_test_3000","sv") \
.setInputCols(["audio_assembler"]) \
.setOutputCol("text")
pipeline = Pipeline().setStages([audioAssembler, speechToText])
pipelineModel = pipeline.fit(data)
pipelineDF = pipelineModel.transform(data)
val audioAssembler = new AudioAssembler()
.setInputCol("audio_content")
.setOutputCol("audio_assembler")
val speechToText = WhisperForCTC.pretrained("asr_whisper_small_swedish_test_3000","sv")
.setInputCols(Array("audio_assembler"))
.setOutputCol("text")
val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText))
val pipelineModel = pipeline.fit(data)
val pipelineDF = pipelineModel.transform(data)
Model Information
Model Name: | asr_whisper_small_swedish_test_3000 |
Compatibility: | Spark NLP 5.1.4+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [audio_assembler] |
Output Labels: | [text] |
Language: | sv |
Size: | 1.7 GB |
References
https://huggingface.co/ZinebSN/whisper-small-swedish-Test-3000