Instructions to use junsor/whisper-tiny-aishell with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junsor/whisper-tiny-aishell with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="junsor/whisper-tiny-aishell")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("junsor/whisper-tiny-aishell") model = AutoModelForSpeechSeq2Seq.from_pretrained("junsor/whisper-tiny-aishell", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from junsor/whisper-tiny-aishell: direct link, hf CLI and curl.
- Browser
- Download file 2.38 MB
-
https://huggingface.co/junsor/whisper-tiny-aishell/resolve/main/adapter_model.bin
- Command line
-
hf download hf://junsor/whisper-tiny-aishell/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/junsor/whisper-tiny-aishell/resolve/main/adapter_model.bin
2.38 MB
- Xet hash:
- 8f28bfbd87736fe18e947d18bb4a5ab66ddcc931c776f179a1f658b39c998527
- Size of remote file:
- 2.38 MB
- SHA256:
- a824611174f7bd8cd60269df2fa6c11c902fb822a617b2c68d3ebe1d58153a78
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.