Instructions to use ovinduG/multi-domain-classifier-phi3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ovinduG/multi-domain-classifier-phi3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ovinduG/multi-domain-classifier-phi3")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ovinduG/multi-domain-classifier-phi3", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add confusion matrix
Browse files- .gitattributes +1 -0
- confusion_matrix.png +3 -0
.gitattributes
CHANGED
|
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
confusion_matrix.png filter=lfs diff=lfs merge=lfs -text
|
confusion_matrix.png
ADDED
|
Git LFS Details
|