Automatic Speech Recognition
Transformers
ONNX
Arabic
English
whisper
asr
bahraini-arabic
code-switching
fine-tuned
Instructions to use Fatimaa75/whisper-base-bahraini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fatimaa75/whisper-base-bahraini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Fatimaa75/whisper-base-bahraini")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Fatimaa75/whisper-base-bahraini") model = AutoModelForSpeechSeq2Seq.from_pretrained("Fatimaa75/whisper-base-bahraini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer_config.json with huggingface_hub
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
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@@ -124,4 +124,4 @@
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"task": "transcribe",
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"tokenizer_class": "WhisperTokenizer",
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"unk_token": "<|endoftext|>"
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}
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"task": "transcribe",
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"tokenizer_class": "WhisperTokenizer",
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"unk_token": "<|endoftext|>"
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}
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