Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Tamil
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use BadBoy17G/whisper-tiny-custom-test-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BadBoy17G/whisper-tiny-custom-test-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="BadBoy17G/whisper-tiny-custom-test-final")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("BadBoy17G/whisper-tiny-custom-test-final") model = AutoModelForSpeechSeq2Seq.from_pretrained("BadBoy17G/whisper-tiny-custom-test-final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BadBoy17G/whisper-tiny-custom-test-final: direct link, hf CLI and curl.
- Browser
- Download file 4.41 kB
-
https://huggingface.co/BadBoy17G/whisper-tiny-custom-test-final/resolve/main/training_args.bin
- Command line
-
hf download hf://BadBoy17G/whisper-tiny-custom-test-final/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BadBoy17G/whisper-tiny-custom-test-final/resolve/main/training_args.bin
4.41 kB
- Xet hash:
- 046122587455513d15949a431d00e0cfe8f684d761970d5f965bada8707c0b44
- Size of remote file:
- 4.41 kB
- SHA256:
- b3040d1129c76a3fd6447202b79fb2ace3febe8774611a42b4d9aa5f9d0efce6
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