| --- |
| library_name: transformers |
| tags: [] |
| --- |
| |
| # Model Card for Model ID |
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| <!-- Provide a quick summary of what the model is/does. --> |
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| ## Model Details |
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| ### Model Description |
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| This is a quantized model of the original version mohammed/whisper-small-arabic-cv-11 |
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| - **Developed by:** Mohammed Bakheet |
| - **Funded by [optional]:** Kalam Technology |
| - **Language(s) (NLP):** Arabic, English |
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| ## Uses |
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| This a quantized model that reads arabic voice and transcribes/translate it into english |
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| ### Direct Use |
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| First, install the following packages using the following commands: |
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| pip install -U optimum[exporters,onnxruntime] transformers |
| pip install huggingface_hub |
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| ```python |
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| # uncomment the following installation if you are using a notebook: |
| #!pip install -U optimum[exporters,onnxruntime] transformers |
| #!pip install huggingface_hub |
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|
| # import the required packages |
| from optimum.onnxruntime import ORTModelForSpeechSeq2Seq |
| from transformers import WhisperTokenizerFast, WhisperFeatureExtractor, pipeline |
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| # set model name/id |
| model_name = 'mohammed/quantized-whisper-small' # folder name |
| model = ORTModelForSpeechSeq2Seq.from_pretrained(model_name, export=False) |
| tokenizer = WhisperTokenizerFast.from_pretrained(model_name) |
| feature_extractor = WhisperFeatureExtractor.from_pretrained(model_name) |
| forced_decoder_ids = tokenizer.get_decoder_prompt_ids(language="ar", task="transcribe") |
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| pipe = pipeline('automatic-speech-recognition', |
| model=model, |
| tokenizer=tokenizer, |
| feature_extractor=feature_extractor, |
| model_kwargs={"forced_decoder_ids": forced_decoder_ids}) |
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| # the file to be transcribed |
| pipe('Recording.mp3') |
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| ``` |
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| ### Out-of-Scope Use |
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| <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
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| The model does a direct translation of Arabic speech, and doesn't do a direct transcription, we are still working on that. |
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| ### Recommendations |
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| <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
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| Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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| ## How to Get Started with the Model |
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| Use the code below to get started with the model. |
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| ```python |
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| First, install the following packages using the following commands: |
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| pip install -U optimum[exporters,onnxruntime] transformers |
| pip install huggingface_hub |
| |
| from optimum.onnxruntime import ORTModelForSpeechSeq2Seq |
| from transformers import WhisperTokenizerFast, WhisperFeatureExtractor, pipeline |
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| model_name = 'mohammed/quantized-whisper-small' # folder name |
| model = ORTModelForSpeechSeq2Seq.from_pretrained(model_name, export=False) |
| tokenizer = WhisperTokenizerFast.from_pretrained(model_name) |
| feature_extractor = WhisperFeatureExtractor.from_pretrained(model_name) |
| forced_decoder_ids = tokenizer.get_decoder_prompt_ids(language="ar", task="transcribe") |
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| pipe = pipeline('automatic-speech-recognition', |
| model=model, |
| tokenizer=tokenizer, |
| feature_extractor=feature_extractor, |
| model_kwargs={"forced_decoder_ids": forced_decoder_ids}) |
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| # the file to be transcribed |
| pipe('Recording.mp3') |
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| ``` |
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| ### Training Data |
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| Please refer to the original model at "mohammed/whisper-small-arabic-cv-11" |
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| ### Training Procedure |
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| Please refer to the original model at "mohammed/whisper-small-arabic-cv-11" |
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| #### Preprocessing [optional] |
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| Please refer to the original model at "mohammed/whisper-small-arabic-cv-11" |
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| #### Training Hyperparameters |
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| - **Training regime:** Please refer to the original model at "mohammed/whisper-small-arabic-cv-11" |
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