Instructions to use Achitha/ta-eng-data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Achitha/ta-eng-data with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Achitha/ta-eng-data")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Achitha/ta-eng-data") model = AutoModelForSpeechSeq2Seq.from_pretrained("Achitha/ta-eng-data", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd2beb9eb60394feb56338db4c44c35889785cd79227680257c7afb3220b67e0
- Size of remote file:
- 290 MB
- SHA256:
- c0ae5e1c3656c53b771151d344cd2ae276e353940e881fd72a91d8174cb11364
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