Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
English
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use genevera/whisper-medium.en-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use genevera/whisper-medium.en-ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="genevera/whisper-medium.en-ft")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("genevera/whisper-medium.en-ft") model = AutoModelForSpeechSeq2Seq.from_pretrained("genevera/whisper-medium.en-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5f1be112a7371d0adbf109467f1edd99fcde9f041f8f50bd8526e65d014c7a2
- Size of remote file:
- 3.71 kB
- SHA256:
- 782397da83f9c975cf4f3c79fead8ab48c8e0af4674b934076164877927a4b21
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