Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use tomerz14/whisper-tiny-en-US with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tomerz14/whisper-tiny-en-US with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="tomerz14/whisper-tiny-en-US")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("tomerz14/whisper-tiny-en-US") model = AutoModelForSpeechSeq2Seq.from_pretrained("tomerz14/whisper-tiny-en-US", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tomerz14/whisper-tiny-en-US: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/tomerz14/whisper-tiny-en-US/resolve/main/training_args.bin
- Command line
-
hf download hf://tomerz14/whisper-tiny-en-US/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tomerz14/whisper-tiny-en-US/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- b328b1040ee11ef566e88ce9fd2be66728ff3665335bb8e65f44fd0a09583018
- Size of remote file:
- 5.5 kB
- SHA256:
- 4b6a477672bf13a5e65833511f9f5c24e49e9aac8694a113a41e192b1f8a46a0
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