Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2-bert
Generated from Trainer
Instructions to use cportoca/CS224S_Quechua_Project_Expanded_Dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cportoca/CS224S_Quechua_Project_Expanded_Dataset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cportoca/CS224S_Quechua_Project_Expanded_Dataset")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("cportoca/CS224S_Quechua_Project_Expanded_Dataset") model = AutoModelForCTC.from_pretrained("cportoca/CS224S_Quechua_Project_Expanded_Dataset", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3cfa76533063bc9e61b2ea353690a8aa8c90bad0dc2d181b7e5f2f9ecb082292
- Size of remote file:
- 4.98 kB
- SHA256:
- c7406880dae07494b004ca2e63b4ed65768186c7118292ae303d5c142991628c
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