Datasets:

cardiffnlp
/

tweet_topic_multi

Tasks:

Text Classification

Sub-tasks:

sentiment-classification

Languages:

Multilinguality:

Size Categories:

ArXiv:

License:

Dataset card Files Files and versions Community

asahi417 commited on Sep 29, 2022

Commit

41ff77b

•

1 Parent(s): b0f3e5c

Update readme.py

Files changed (1) hide show

readme.py +2 -2

readme.py CHANGED Viewed

@@ -1,6 +1,6 @@
 import os
 from typing import Dict
 bib = """
 @inproceedings{dimosthenis-etal-2022-twitter,
     title = "{T}witter {T}opic {C}lassification",
@@ -83,7 +83,7 @@ model.eval()
 class_mapping = model.config.id2label
 with torch.no_grad():
-  text = "#NewVideo Cray Dollas- Water- Ft. Charlie Rose- (Official Music Video)- {{URL}} via {@YouTube@} #watchandlearn {{USERNAME}}"
   tokens = tokenizer(text, return_tensors='pt')
   output = model(**tokens)
   flags = [sigmoid(s) > 0.5 for s in output[0][0].detach().tolist()]

 import os
 from typing import Dict
+sample = "#NewVideo Cray Dollas- Water- Ft. Charlie Rose- (Official Music Video)- {{URL}} via {@YouTube@} #watchandlearn {{USERNAME}}"
 bib = """
 @inproceedings{dimosthenis-etal-2022-twitter,
     title = "{T}witter {T}opic {C}lassification",
 class_mapping = model.config.id2label
 with torch.no_grad():
+  text = {sample}
   tokens = tokenizer(text, return_tensors='pt')
   output = model(**tokens)
   flags = [sigmoid(s) > 0.5 for s in output[0][0].detach().tolist()]