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:
- c9aa0a84c25b74333d2fbf4eca08d4730329cfdb83c2da65841f29ddbbab67fb
- Size of remote file:
- 3.64 kB
- SHA256:
- 2a96810b985fbc0336da211a8d49a816cde166b41b0762a0a879a2f4f96a9801
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