Feature Extraction
Transformers
Safetensors
English
usad
automatic-speech-recognition
audio-classification
audio
speech
music
custom_code
Instructions to use MIT-SLS/USAD-Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MIT-SLS/USAD-Small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MIT-SLS/USAD-Small", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MIT-SLS/USAD-Small", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Change license
Browse files
README.md
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
---
|
| 2 |
-
license:
|
| 3 |
pipeline_tag: feature-extraction
|
| 4 |
tags:
|
| 5 |
- automatic-speech-recognition
|
|
@@ -89,4 +89,4 @@ See [usad_model.py](https://huggingface.co/MIT-SLS/USAD-Small/blob/main/usad_mod
|
|
| 89 |
|
| 90 |
## 🙏 Acknowledgement
|
| 91 |
|
| 92 |
-
Our implementation is based on the awesome [facebookresearch/fairseq](https://github.com/facebookresearch/fairseq), [cwx-worst-one/EAT](https://github.com/cwx-worst-one/EAT), and [sooftware/conformer](https://github.com/sooftware/conformer) repositories.
|
|
|
|
| 1 |
---
|
| 2 |
+
license: cc-by-nc-sa-4.0
|
| 3 |
pipeline_tag: feature-extraction
|
| 4 |
tags:
|
| 5 |
- automatic-speech-recognition
|
|
|
|
| 89 |
|
| 90 |
## 🙏 Acknowledgement
|
| 91 |
|
| 92 |
+
Our implementation is based on the awesome [facebookresearch/fairseq](https://github.com/facebookresearch/fairseq), [cwx-worst-one/EAT](https://github.com/cwx-worst-one/EAT), and [sooftware/conformer](https://github.com/sooftware/conformer) repositories.
|