Instructions to use safe-models/ContentVec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use safe-models/ContentVec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="safe-models/ContentVec")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("safe-models/ContentVec") model = AutoModel.from_pretrained("safe-models/ContentVec") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -16,8 +16,8 @@ from transformers import AutoProcessor, HubertModel
|
|
| 16 |
import librosa
|
| 17 |
|
| 18 |
# Load the processor and model
|
| 19 |
-
processor = AutoProcessor.from_pretrained("
|
| 20 |
-
hubert = HubertModel.from_pretrained("
|
| 21 |
|
| 22 |
# Read the audio
|
| 23 |
audio, sr = librosa.load("test.wav", sr=16000)
|
|
|
|
| 16 |
import librosa
|
| 17 |
|
| 18 |
# Load the processor and model
|
| 19 |
+
processor = AutoProcessor.from_pretrained("safe-models/ContentVec")
|
| 20 |
+
hubert = HubertModel.from_pretrained("safe-models/ContentVec")
|
| 21 |
|
| 22 |
# Read the audio
|
| 23 |
audio, sr = librosa.load("test.wav", sr=16000)
|