Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Bagus/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bagus/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Bagus/whisper-tiny-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Bagus/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("Bagus/whisper-tiny-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Bagus/whisper-tiny-en: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/Bagus/whisper-tiny-en/resolve/main/training_args.bin
- Command line
-
hf download hf://Bagus/whisper-tiny-en/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Bagus/whisper-tiny-en/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 02203313a3bec656de1266b095d8499e12cfdd67b8c84239984c15569cc5d22d
- Size of remote file:
- 4.73 kB
- SHA256:
- aa24605a87bc9f17d9af87abe7faefec380b528d7ac6e0c6ec6373f389ca3fb8
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