Instructions to use arthoho66/model_test_002 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arthoho66/model_test_002 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="arthoho66/model_test_002")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("arthoho66/model_test_002") model = AutoModelForSpeechSeq2Seq.from_pretrained("arthoho66/model_test_002", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17062e3d56fb480bc994ec41e02e4489d8e5b0c3d8f405865260abfabacdff0d
- Size of remote file:
- 6.11 GB
- SHA256:
- 6f533870c97dfdbd91371536045a7db5e749317952376315010697bafee24a61
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