Instructions to use hf-internal-testing/tiny-random-Wav2Vec2ConformerForCTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Wav2Vec2ConformerForCTC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-internal-testing/tiny-random-Wav2Vec2ConformerForCTC")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ConformerForCTC") model = AutoModelForCTC.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ConformerForCTC") - Notebooks
- Google Colab
- Kaggle
[Awaiting approval] Upload ONNX weights
#2 opened about 2 years ago
by
Xenova
Adding `safetensors` variant of this model
#1 opened about 2 years ago
by
SFconvertbot