Instructions to use arthoho66/model_005_2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arthoho66/model_005_2000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="arthoho66/model_005_2000")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("arthoho66/model_005_2000") model = AutoModelForSpeechSeq2Seq.from_pretrained("arthoho66/model_005_2000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c36b32367dfc50ccb4c61cee065133c589da3a3715638a70e6971da2bd72e8f3
- Size of remote file:
- 3.06 GB
- SHA256:
- 1c2ce053c8c6402c0eafebd60a4301d6b08b43320ab00dd407dab58320f39919
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