Create README.md
Browse files
README.md
ADDED
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
language:
|
3 |
+
- en
|
4 |
+
metrics:
|
5 |
+
- accuracy
|
6 |
+
- f1
|
7 |
+
library_name: transformers
|
8 |
+
pipeline_tag: token-classification
|
9 |
+
tags:
|
10 |
+
- deberta-v3
|
11 |
+
---
|
12 |
+
|
13 |
+
## Deberta for Named Entity Recognition
|
14 |
+
|
15 |
+
I used a Pretrained Deberta-v3-base and finetuned it on Few-NERD, A NER dataset that contains over 180k examples and over 4.6 million tokens.
|
16 |
+
|
17 |
+
The Token labels are Person, Organisation, Location, Building, Event, Product, Art & Misc.
|
18 |
+
|
19 |
+
## How to use the model
|
20 |
+
|
21 |
+
```python
|
22 |
+
from transformers import pipeline
|
23 |
+
pipe = pipeline(model='RashidNLP/NER-Deberta')
|
24 |
+
pipe(["Elon Musk will be at SpaceX's Starbase facility in Boca Chica for the orbital launch of starship next month"])
|
25 |
+
```
|