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  ### Model Description
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- <!-- Provide a longer summary of what this model is. -->
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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-
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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  ### Model Sources [optional]
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  ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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  ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
 
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- [More Information Needed]
 
 
 
 
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- ### Downstream Use [optional]
 
 
 
 
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
 
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- [More Information Needed]
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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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- [More Information Needed]
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-
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- ## Bias, Risks, and Limitations
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-
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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  ### Recommendations
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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
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+ - **Funded by [optional]:** Kalam Technology
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+ - **Language(s) (NLP):** Arabic, English
 
 
 
 
 
 
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  ### Model Sources [optional]
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  ## Uses
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+ This a quantized model that read arabic voice and transcribes/translate it into english
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  ### Direct Use
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+ ```python
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+ from optimum.onnxruntime import ORTModelForSpeechSeq2Seq
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+ from transformers import WhisperTokenizerFast, WhisperFeatureExtractor, pipeline
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+ model_name = 'mohammed/quantized-whisper-small' # folder name
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+ model = ORTModelForSpeechSeq2Seq.from_pretrained(model_name, export=False)
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+ tokenizer = WhisperTokenizerFast.from_pretrained(model_name)
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+ feature_extractor = WhisperFeatureExtractor.from_pretrained(model_name)
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+ forced_decoder_ids = tokenizer.get_decoder_prompt_ids(language="ar", task="transcribe")
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+ pipe = pipeline('automatic-speech-recognition',
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+ model=model,
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+ tokenizer=tokenizer,
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+ feature_extractor=feature_extractor,
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+ model_kwargs={"forced_decoder_ids": forced_decoder_ids})
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+ # the file to be transcribed
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+ 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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