Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Hebrew
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use Shiry/whisper-large-v2-he-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shiry/whisper-large-v2-he-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Shiry/whisper-large-v2-he-1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Shiry/whisper-large-v2-he-1") model = AutoModelForSpeechSeq2Seq.from_pretrained("Shiry/whisper-large-v2-he-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Shiry/whisper-large-v2-he-1: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/Shiry/whisper-large-v2-he-1/resolve/main/training_args.bin
- Command line
-
hf download hf://Shiry/whisper-large-v2-he-1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Shiry/whisper-large-v2-he-1/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- b4b0fbb835a1d4a551dcad5f969ccd5695878a2eb59b978fc43e8b76728fa21b
- Size of remote file:
- 3.58 kB
- SHA256:
- 1956b50b650f339efcdb77362b0bb5d7946e7d7e944920f743987ae791089cff
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