Instructions to use scribe-project/wav2vec2-large-voxrex-300m-radio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scribe-project/wav2vec2-large-voxrex-300m-radio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="scribe-project/wav2vec2-large-voxrex-300m-radio")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("scribe-project/wav2vec2-large-voxrex-300m-radio") model = AutoModelForCTC.from_pretrained("scribe-project/wav2vec2-large-voxrex-300m-radio", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9526cd4e4517ebd780777dbd0056a49670e24d4f32f66ed5dff8509d11a35ed5
- Size of remote file:
- 3.58 kB
- SHA256:
- 32aa3f1fe6b577755f31c59ec1fb61d9cd24fc0e15210ae85c5caaedfae3d0ba
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.