Instructions to use KevinGeng/Tony1_AVA_script_conv_train_conv_dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KevinGeng/Tony1_AVA_script_conv_train_conv_dev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="KevinGeng/Tony1_AVA_script_conv_train_conv_dev")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("KevinGeng/Tony1_AVA_script_conv_train_conv_dev") model = AutoModelForSpeechSeq2Seq.from_pretrained("KevinGeng/Tony1_AVA_script_conv_train_conv_dev") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41a1b5897d22c4e5e00c4dc12815e7b7b88e123cd78cf2dd2448e92e4b8d1507
- Size of remote file:
- 3.06 GB
- SHA256:
- a71da8c0afa759b36eb44198a105d3b2ae6ebd971e69934316d018da36c38c81
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