Instructions to use midoiv/result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use midoiv/result with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="midoiv/result")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("midoiv/result") model = AutoModelForAudioClassification.from_pretrained("midoiv/result", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
runs/Apr03_20-19-54_5a3e4246b5e5/events.out.tfevents.1712175610.5a3e4246b5e5.17.0
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 sha256:313189a16ba10b5d13fc80868bcb6a8021d5f6188a781232be244f039fc675c3
|
| 3 |
+
size 45433
|