Instructions to use CollectionStudio/whisper-large-v3-turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CollectionStudio/whisper-large-v3-turbo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="CollectionStudio/whisper-large-v3-turbo")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("CollectionStudio/whisper-large-v3-turbo") model = AutoModelForSpeechSeq2Seq.from_pretrained("CollectionStudio/whisper-large-v3-turbo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from CollectionStudio/whisper-large-v3-turbo: direct link, hf CLI and curl.
- Browser
- Download file 2.71 MB
-
https://huggingface.co/CollectionStudio/whisper-large-v3-turbo/resolve/main/tokenizer.json
- Command line
-
hf download hf://CollectionStudio/whisper-large-v3-turbo/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/CollectionStudio/whisper-large-v3-turbo/resolve/main/tokenizer.json
2.71 MB
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