Instructions to use TenzinGayche/wav2vec2-test-for-continue-training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TenzinGayche/wav2vec2-test-for-continue-training with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TenzinGayche/wav2vec2-test-for-continue-training")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("TenzinGayche/wav2vec2-test-for-continue-training") model = AutoModelForCTC.from_pretrained("TenzinGayche/wav2vec2-test-for-continue-training", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:888961117ae98990af018180247347916a9f9e200f00b11a17614d3f5b03db5b
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size 1262278932
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