Instructions to use ai-project/wav2vec2-xlsr-large-vi-aiclass-20221-group-8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ai-project/wav2vec2-xlsr-large-vi-aiclass-20221-group-8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ai-project/wav2vec2-xlsr-large-vi-aiclass-20221-group-8")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ai-project/wav2vec2-xlsr-large-vi-aiclass-20221-group-8") model = AutoModelForCTC.from_pretrained("ai-project/wav2vec2-xlsr-large-vi-aiclass-20221-group-8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc2330dc47fa52959aa7842baf18314091b47a66c51334922574fed43194f731
- Size of remote file:
- 1.26 GB
- SHA256:
- 6d209eb37ee853e37a22572fc366454333c976532449a7b92a3a74e1173d3d7a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.