Instructions to use Bagus/hubert_xlarge_emodb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bagus/hubert_xlarge_emodb with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Bagus/hubert_xlarge_emodb") model = AutoModel.from_pretrained("Bagus/hubert_xlarge_emodb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 5
Browse files- pytorch_model.bin +1 -1
- training_args.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 3856850802
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9e4b2925c59811f4395d9e8a9aded6c63fd30bce4ef2066291db5639758736d2
|
| 3 |
size 3856850802
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 4536
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1c4802d95a131cd5c07af0d49487e9a039c3a07561a9989be7552b722d55019b
|
| 3 |
size 4536
|