Spaces:
Running
on
Zero
Running
on
Zero
| import spaces | |
| from transformers import pipeline | |
| def classify(tweet, event_model, hftoken): | |
| # event type prediction | |
| event_predictor = pipeline(task="text-classification", model=event_model, | |
| batch_size=512, token=hftoken) | |
| tokenizer_kwargs = {'padding': True, 'truncation': True, 'max_length': 512} | |
| results = {"text": None, "event": None, "score": None} | |
| prediction = event_predictor(tweet, **tokenizer_kwargs)[0] | |
| results["text"] = tweet | |
| results["event"] = prediction["label"] | |
| results["score"] = prediction["score"] | |
| return results |