Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Maimonator/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maimonator/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Maimonator/whisper-tiny-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Maimonator/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("Maimonator/whisper-tiny-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Maimonator/whisper-tiny-en: direct link, hf CLI and curl.
- Browser
- Download file 3.77 kB
-
https://huggingface.co/Maimonator/whisper-tiny-en/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Maimonator/whisper-tiny-en@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Maimonator/whisper-tiny-en/resolve/refs%2Fpr%2F1/training_args.bin
3.77 kB
- Xet hash:
- 63f6fa3bc0530e0b746df8e1a6c5c495d27922fb3503eef617c2a05ce1d62ad0
- Size of remote file:
- 3.77 kB
- SHA256:
- f1b2b25a852201ee7f0b8717301095644a8dcc3830ee06c7e856f51e53006569
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