Instructions to use Toadoum/swa-checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Toadoum/swa-checkpoint with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("Toadoum/swa-checkpoint") model = AutoModelForPreTraining.from_pretrained("Toadoum/swa-checkpoint") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +1 -1
config.json
CHANGED
|
@@ -83,7 +83,7 @@
|
|
| 83 |
"speaking_rate": 1.0,
|
| 84 |
"spectrogram_bins": 513,
|
| 85 |
"torch_dtype": "float32",
|
| 86 |
-
"transformers_version": "4.
|
| 87 |
"upsample_initial_channel": 512,
|
| 88 |
"upsample_kernel_sizes": [
|
| 89 |
16,
|
|
|
|
| 83 |
"speaking_rate": 1.0,
|
| 84 |
"spectrogram_bins": 513,
|
| 85 |
"torch_dtype": "float32",
|
| 86 |
+
"transformers_version": "4.53.0",
|
| 87 |
"upsample_initial_channel": 512,
|
| 88 |
"upsample_kernel_sizes": [
|
| 89 |
16,
|