Automatic Speech Recognition
Transformers
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use emptx/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emptx/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="emptx/whisper-tiny-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("emptx/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("emptx/whisper-tiny-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from emptx/whisper-tiny-en: direct link, hf CLI and curl.
- Browser
- Download file 5.33 kB
-
https://huggingface.co/emptx/whisper-tiny-en/resolve/main/training_args.bin
- Command line
-
hf download hf://emptx/whisper-tiny-en/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/emptx/whisper-tiny-en/resolve/main/training_args.bin
5.33 kB
- Xet hash:
- 05cdaf46be347cfc78ea569c0c4db0112b48a7d6151a18c443bf040dbb7f5f84
- Size of remote file:
- 5.33 kB
- SHA256:
- 6052bcc667a3bec409435daa5e25945047dcddadf2245294b297369cf1a0ebd4
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