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--- |
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license: apache-2.0 |
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base_model: |
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- openai/whisper-base |
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pipeline_tag: automatic-speech-recognition |
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language: |
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- en |
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- ru |
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--- |
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OpenAI Whisper base [model](https://huggingface.co/openai/whisper-base) converted to ONNX format for [onnx-asr](https://github.com/istupakov/onnx-asr). |
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Install onnx-asr |
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```shell |
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pip install onnx-asr[cpu,hub] |
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``` |
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Load whisper-base model and recognize wav file |
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```py |
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import onnx_asr |
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model = onnx_asr.load_model("whisper-base") |
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print(model.recognize("test.wav")) |
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``` |
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## Model export |
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Read onnxruntime [instruction](https://github.com/microsoft/onnxruntime/blob/main/onnxruntime/python/tools/transformers/models/whisper/README.md) for convert Whisper to ONNX. |
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Download model and export with *Beam Search* and *Forced Decoder Input Ids*: |
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```shell |
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python3 -m onnxruntime.transformers.models.whisper.convert_to_onnx -m openai/whisper-base --output ./whisper-onnx --use_forced_decoder_ids --optimize_onnx --precision fp32 |
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``` |
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Save tokenizer config |
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```py |
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from transformers import WhisperTokenizer |
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processor = WhisperTokenizer.from_pretrained("openai/whisper-base") |
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processor.save_pretrained("whisper-onnx") |
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``` |
