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:
- a8a169633faf5134ad25759bc2b7af24e9fbce00900a0c6884a182d45fb207b2
- Size of remote file:
- 3.64 kB
- SHA256:
- 8cfc387dfbd35d46f9723fd4f70b2fe9fe86bf6056ed7312a7fa14a9d265ecae
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