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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 131 Bytes
a2ecb29 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:bf2595c5dcc936ba065596d74a3fbbbb655a0dc1a7ecce55a706520b0369caf1
size 203041
|