Instructions to use KevinGeng/Negel_152_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/Negel_152_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/Negel_152_AVA_script_conv_train_conv_dev")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("KevinGeng/Negel_152_AVA_script_conv_train_conv_dev") model = AutoModelForSpeechSeq2Seq.from_pretrained("KevinGeng/Negel_152_AVA_script_conv_train_conv_dev") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f7da7c3023286b6cecd01e5e62323da03a1856f36b9d6804282cce427538f8d
- Size of remote file:
- 3.76 kB
- SHA256:
- a9cd40bce7dad0e380ccf50a705e66221c7b6f41ddae17e88cc948445df529a9
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