Instructions to use ashwin123/whisper-tiny-ml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashwin123/whisper-tiny-ml with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ashwin123/whisper-tiny-ml")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ashwin123/whisper-tiny-ml") model = AutoModelForSpeechSeq2Seq.from_pretrained("ashwin123/whisper-tiny-ml", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ashwin123/whisper-tiny-ml: direct link, hf CLI and curl.
- Browser
- Download file 151 MB
-
https://huggingface.co/ashwin123/whisper-tiny-ml/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ashwin123/whisper-tiny-ml/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ashwin123/whisper-tiny-ml/resolve/main/pytorch_model.bin
151 MB
- Xet hash:
- 05f2e59e970fc8b9b024e46f6aacffc64197d4562e5c36b395fc3fcfbce6bef1
- Size of remote file:
- 151 MB
- SHA256:
- 874611c7cbe196c0b9f6e4333161a0c32c533687cecac4cb7d6ab583aa6be62e
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