Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Malayalam
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use thennal/whisper-medium-ml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thennal/whisper-medium-ml with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="thennal/whisper-medium-ml")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("thennal/whisper-medium-ml") model = AutoModelForSpeechSeq2Seq.from_pretrained("thennal/whisper-medium-ml", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#3
by librarian-bot - opened
README.md
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@@ -14,6 +14,7 @@ datasets:
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- thennal/indic_tts_ml
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metrics:
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- wer
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model-index:
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- name: Whisper Medium Malayalam - Thennal D K
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results:
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- thennal/indic_tts_ml
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metrics:
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- wer
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base_model: openai/whisper-medium
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model-index:
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- name: Whisper Medium Malayalam - Thennal D K
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results:
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