Instructions to use jdmartinev/CREMA_D_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jdmartinev/CREMA_D_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="jdmartinev/CREMA_D_Model")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("jdmartinev/CREMA_D_Model") model = AutoModelForAudioClassification.from_pretrained("jdmartinev/CREMA_D_Model") - Notebooks
- Google Colab
- Kaggle
Commit ·
435767b
1
Parent(s): 1136c0b
End of training
Browse files
runs/May03_20-45-16_2957c7b25484/events.out.tfevents.1683146727.2957c7b25484.31.2
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:50e92991fc646678f532d52a0f1b0f7369bbfe1234df795ca75a72b2888cca6b
|
| 3 |
+
size 155449
|