Instructions to use sheenrooff/small_audio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sheenrooff/small_audio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sheenrooff/small_audio")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sheenrooff/small_audio") model = AutoModelForSpeechSeq2Seq.from_pretrained("sheenrooff/small_audio", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sheenrooff/small_audio: direct link, hf CLI and curl.
- Browser
- Download file 967 MB
-
https://huggingface.co/sheenrooff/small_audio/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sheenrooff/small_audio/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sheenrooff/small_audio/resolve/main/pytorch_model.bin
967 MB
- Xet hash:
- 9992ae0b3efad25ccc3a84dac9254a629a84fbfd83f14a91ca8dc95474af44fa
- Size of remote file:
- 967 MB
- SHA256:
- b2b8f8a6d32caf0ac6fa6f47999be9e0a70def1bec9e5dbbde7b7099547b4983
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