Instructions to use orkidea/whisper-small-guc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use orkidea/whisper-small-guc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="orkidea/whisper-small-guc")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("orkidea/whisper-small-guc") model = AutoModelForSpeechSeq2Seq.from_pretrained("orkidea/whisper-small-guc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 478893555c1aa7a82c917b4eaf856b43a18aca80ee19fe84d8bc2f821a3bc914
- Size of remote file:
- 967 MB
- SHA256:
- a9cd7b169c63cca2769a207b2fe41249c0a159c64560a503d87f2a41e7991b85
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