Instructions to use PThi35/whisper_large_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PThi35/whisper_large_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="PThi35/whisper_large_v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("PThi35/whisper_large_v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("PThi35/whisper_large_v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0a988440bffd54d09f8030c3712e8eb6af61ed793c42348d0d1345a1750a820
- Size of remote file:
- 5.97 kB
- SHA256:
- ca0d59febb42f091985e8ddc744f3360a1ecc2c99f651eb1eb0d31fae401d447
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