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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d60f81ba190a8f6e74c41f28968aa6bdbb489e277818b587357a8d1adc8a4b6
- Size of remote file:
- 3.76 kB
- SHA256:
- ddb8719e08d25214ef2579dbbb99f4c8adc901fe09236856ed81cf4db3a22596
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