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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b326b52c817fdb0df1d322b0e9176f41ff73f081dfca61e731254b01b5a79162
- Size of remote file:
- 290 MB
- SHA256:
- d4d64eaf9ae3afca412867b9bfa2586df8bc594d69d60a44819b946063cde73d
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