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:
- e62dd79e63f7efb077f7482008882c247b835078269251d2fb95074d2f44c4e9
- Size of remote file:
- 3.06 GB
- SHA256:
- 6382b40fac6745ee10938074219c0b3ab747539b3c176749aa5bc41b67bd02fd
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