Instructions to use Achitha/small_data_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Achitha/small_data_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Achitha/small_data_test")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Achitha/small_data_test") model = AutoModelForSpeechSeq2Seq.from_pretrained("Achitha/small_data_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b9cc011410f9e64c285e30b6e7b9a16acb17003d610720a60cff7edcacca84f
- Size of remote file:
- 290 MB
- SHA256:
- e68ceb65fe4447a3fd494cc01d19cc122e78915ce71e1770a8317222c99f8839
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