Instructions to use mispeech/ced-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mispeech/ced-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="mispeech/ced-small", trust_remote_code=True)# Load model directly from transformers import AutoModelForAudioClassification model = AutoModelForAudioClassification.from_pretrained("mispeech/ced-small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
5d7ba90
1
Parent(s): 67b888c
Update README.md
Browse files
README.md
CHANGED
|
@@ -27,7 +27,10 @@ Augmentation and knowledge distillation (KD) are well-established techniques emp
|
|
| 27 |
|
| 28 |
## Uses
|
| 29 |
|
| 30 |
-
|
|
|
|
|
|
|
|
|
|
| 31 |
|
| 32 |
```python
|
| 33 |
>>> from ced_model.feature_extraction_ced import CedFeatureExtractor
|
|
|
|
| 27 |
|
| 28 |
## Uses
|
| 29 |
|
| 30 |
+
```bash
|
| 31 |
+
git lfs install
|
| 32 |
+
git clone https://huggingface.co/mispeech/ced-small
|
| 33 |
+
```
|
| 34 |
|
| 35 |
```python
|
| 36 |
>>> from ced_model.feature_extraction_ced import CedFeatureExtractor
|