Instructions to use privacy-tech-lab/LngDistilledModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/LngDistilledModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/LngDistilledModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/LngDistilledModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/LngDistilledModel") - Notebooks
- Google Colab
- Kaggle
Commit ·
c1db4ae
1
Parent(s): 95623de
Create README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
widget:
|
| 3 |
+
- text: "'a\\\\\",\\\\\"zipcode\\\\\":\\\\\"130 00\\\\\",\\\\\"timezone\\\\\":\\\\\"Europe/Prague\\\\\",\\\\\"latitude\\\\\":\\\\\"50.08040\\\\\",\\\\\"longitude\\\\\":\\\\\"<TARGET_LNG>\\\\\",\\\\\"city\\\\\":\\\\\"Prague\\\\\",\\\\\"continent\\\\\":\\\\\"EU\\\\\"}\",\"czprg_37\":\"!function(){var e={64515:function(e,t,n){\\\\'"
|
| 4 |
+
example_title: "Lng True Positive Example"
|
| 5 |
+
- text: "'Al Moalla\\\\\"},{\\\\\"centroid\\\\\":\\\\\"POINT(55.591619 25.50406)\\\\\",\\\\\"geometry\\\\\":\\\\\"POLYGON((<TARGET_LNG> 25.447356,55.54679 25.541579,55.723851 25.541579,55.723851 25.447356,55.54679 25.447356))\\\\\",\\\\\"id\\\\\":\\\\\"70030076164683501'"
|
| 6 |
+
example_title: "Lng False Positive Example"
|
| 7 |
+
---
|