Instructions to use Wikidepia/w2v2-id-tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wikidepia/w2v2-id-tmp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Wikidepia/w2v2-id-tmp")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Wikidepia/w2v2-id-tmp") model = AutoModelForCTC.from_pretrained("Wikidepia/w2v2-id-tmp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0e67930b931ca82713c384d0d2cda46ceb8c83c06ab65529d3ac8b4138998c6
- Size of remote file:
- 1.26 GB
- SHA256:
- 372f4a4122cfdee330b076fe1491643a709fecd1ca2a1568be66634b9ca84fc5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.