Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
whisper-event
Generated from Trainer
hf-asr-leaderboard
pashto
ps
Eval Results (legacy)
Instructions to use ihanif/whisper-medium-pashto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ihanif/whisper-medium-pashto with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ihanif/whisper-medium-pashto")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ihanif/whisper-medium-pashto") model = AutoModelForSpeechSeq2Seq.from_pretrained("ihanif/whisper-medium-pashto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- whisper-event
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- generated_from_trainer
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- hf-asr-leaderboard
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datasets:
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- google/fleurs
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metrics:
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dataset:
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name: google/fleurs
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type: google/fleurs
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config: ps_af
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split: test
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metrics:
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- name: Wer
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type: wer
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- whisper-event
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- generated_from_trainer
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- hf-asr-leaderboard
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- pashto
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- ps
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datasets:
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- google/fleurs
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metrics:
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dataset:
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name: google/fleurs
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type: google/fleurs
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args: 'config: ps_af, split: test'
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metrics:
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- name: Wer
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type: wer
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