Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Hebrew
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use NS-Y/whisper-tiny-he-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NS-Y/whisper-tiny-he-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NS-Y/whisper-tiny-he-5")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NS-Y/whisper-tiny-he-5") model = AutoModelForSpeechSeq2Seq.from_pretrained("NS-Y/whisper-tiny-he-5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from NS-Y/whisper-tiny-he-5: direct link, hf CLI and curl.
- Browser
- Download file 3.77 kB
-
https://huggingface.co/NS-Y/whisper-tiny-he-5/resolve/main/training_args.bin
- Command line
-
hf download hf://NS-Y/whisper-tiny-he-5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/NS-Y/whisper-tiny-he-5/resolve/main/training_args.bin
3.77 kB
- Xet hash:
- bc9cc307b409f01e4afab6c0f0719cdd3395add8cbf3bb408d073311d5f8c501
- Size of remote file:
- 3.77 kB
- SHA256:
- 5e7856c5a2a34b30a7068423385b4b6028189349a3cfb40425a74ff447fb8984
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