Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Urdu
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use codewithdark/WhisperLiveSubs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codewithdark/WhisperLiveSubs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="codewithdark/WhisperLiveSubs")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("codewithdark/WhisperLiveSubs") model = AutoModelForSpeechSeq2Seq.from_pretrained("codewithdark/WhisperLiveSubs") - Notebooks
- Google Colab
- Kaggle
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README.md
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### Training Data
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The model was fine-tuned on the Mozilla Common Voice dataset, specifically the Urdu subset. The dataset consists of approximately
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#### Preprocessing
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The audio was resampled to 16kHz, and text was tokenized using the Whisper tokenizer configured for Urdu.
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```
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### Training Data
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The model was fine-tuned on the Mozilla Common Voice dataset, specifically the Urdu subset. The dataset consists of approximately 141 hr of transcribed Urdu speech.
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#### Preprocessing
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The audio was resampled to 16kHz, and text was tokenized using the Whisper tokenizer configured for Urdu.
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