Views
No views yet
1from transformers import AutoTokenizer, AutoModelForSequenceClassification, AutoConfig
2import torch.nn.functional as F
3
4tokenizer = AutoTokenizer.from_pretrained("sourabhdattawad/mfc-xlm-roberta")
5config = AutoConfig.from_pretrained("sourabhdattawad/mfc-xlm-roberta")
6model = AutoModelForSequenceClassification.from_pretrained("sourabhdattawad/mfc-xlm-roberta")
7
8news_text = """
9Is the World Economy Sliding Into First Recession Since 2009?
10The global economy is wobbling and whether it topples over is the big question in financial markets, executive suites and the corridors of power.
11"""
12encoded_input = tokenizer(news_text, return_tensors="pt", padding=True, truncation=True)
13logits = model(**encoded_input).logits
14scores = F.sigmoid(logits[0]).detach().numpy()
15frames = [config.id2label[i] for i in range(len(scores)) if scores[i]>0.5]
16print(frames)
17['Economic', 'Capacity and resources']