Instructions to use bgstud/whisper-tiny-libirClean-vs-commonNative with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bgstud/whisper-tiny-libirClean-vs-commonNative with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bgstud/whisper-tiny-libirClean-vs-commonNative")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bgstud/whisper-tiny-libirClean-vs-commonNative") model = AutoModelForSpeechSeq2Seq.from_pretrained("bgstud/whisper-tiny-libirClean-vs-commonNative", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitignore from bgstud/whisper-tiny-libirClean-vs-commonNative: direct link, hf CLI and curl.
- Browser
- Download file 13 Bytes
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https://huggingface.co/bgstud/whisper-tiny-libirClean-vs-commonNative/resolve/main/.gitignore
- Command line
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hf download hf://bgstud/whisper-tiny-libirClean-vs-commonNative/.gitignore
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curl -L -o .gitignore https://huggingface.co/bgstud/whisper-tiny-libirClean-vs-commonNative/resolve/main/.gitignore
13 Bytes
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