Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use rossevine/Model_G_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rossevine/Model_G_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rossevine/Model_G_2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("rossevine/Model_G_2") model = AutoModelForCTC.from_pretrained("rossevine/Model_G_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 3200
Browse files
pytorch_model.bin
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runs/Aug29_22-23-27_hpc-Aquarium2/events.out.tfevents.1693322888.hpc-Aquarium2.3670.0
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