Update app.py
Browse files
app.py
CHANGED
|
@@ -1,9 +1,8 @@
|
|
| 1 |
import gradio as gr
|
| 2 |
-
import spaces
|
| 3 |
from transformers import pipeline
|
| 4 |
|
| 5 |
-
token_skill_classifier = pipeline(model="jjzha/escoxlmr_skill_extraction", aggregation_strategy="first"
|
| 6 |
-
token_knowledge_classifier = pipeline(model="jjzha/escoxlmr_knowledge_extraction", aggregation_strategy="first"
|
| 7 |
|
| 8 |
|
| 9 |
examples = [
|
|
@@ -33,7 +32,6 @@ def aggregate_span(results):
|
|
| 33 |
return new_results
|
| 34 |
|
| 35 |
|
| 36 |
-
@spaces.GPU
|
| 37 |
def ner(text):
|
| 38 |
output_skills = token_skill_classifier(text)
|
| 39 |
for result in output_skills:
|
|
|
|
| 1 |
import gradio as gr
|
|
|
|
| 2 |
from transformers import pipeline
|
| 3 |
|
| 4 |
+
token_skill_classifier = pipeline(model="jjzha/escoxlmr_skill_extraction", aggregation_strategy="first")
|
| 5 |
+
token_knowledge_classifier = pipeline(model="jjzha/escoxlmr_knowledge_extraction", aggregation_strategy="first")
|
| 6 |
|
| 7 |
|
| 8 |
examples = [
|
|
|
|
| 32 |
return new_results
|
| 33 |
|
| 34 |
|
|
|
|
| 35 |
def ner(text):
|
| 36 |
output_skills = token_skill_classifier(text)
|
| 37 |
for result in output_skills:
|