Instructions to use r-sharma-coder/hubert-large-ll60k-librispeech-single-gpu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use r-sharma-coder/hubert-large-ll60k-librispeech-single-gpu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="r-sharma-coder/hubert-large-ll60k-librispeech-single-gpu")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("r-sharma-coder/hubert-large-ll60k-librispeech-single-gpu") model = AutoModelForCTC.from_pretrained("r-sharma-coder/hubert-large-ll60k-librispeech-single-gpu") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("r-sharma-coder/hubert-large-ll60k-librispeech-single-gpu")
model = AutoModelForCTC.from_pretrained("r-sharma-coder/hubert-large-ll60k-librispeech-single-gpu")Quick Links
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="r-sharma-coder/hubert-large-ll60k-librispeech-single-gpu")