Automatic Speech Recognition
Transformers
PyTorch
whisper
audio
speech
wav2vec2
Eval Results (legacy)
Instructions to use devasheeshG/whisper_medium_fp16_transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devasheeshG/whisper_medium_fp16_transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="devasheeshG/whisper_medium_fp16_transformers")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("devasheeshG/whisper_medium_fp16_transformers") model = AutoModelForSpeechSeq2Seq.from_pretrained("devasheeshG/whisper_medium_fp16_transformers") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e61bdc918d0af44551b37c0df1721863dbadff44db0b08dd463af3f9859fb485
- Size of remote file:
- 1.53 GB
- SHA256:
- 9cd029beaad444028f54d80bc602778c48984d0fc5f7d47d7d7030276b13490a
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