Create app.py

app.py

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+import torch
+from transformers import AutoTokenizer, BigBirdForQuestionAnswering
+from datasets import load_dataset
+
+tokenizer = AutoTokenizer.from_pretrained("google/bigbird-roberta-base")
+model = BigBirdForQuestionAnswering.from_pretrained("google/bigbird-roberta-base")
+squad_ds = load_dataset("squad_v2", split="train")
+# select random article and question
+LONG_ARTICLE = squad_ds[81514]["context"]
+QUESTION = squad_ds[81514]["question"]
+QUESTION
+
+inputs = tokenizer(QUESTION, LONG_ARTICLE, return_tensors="pt")
+# long article and question input
+list(inputs["input_ids"].shape)
+
+with torch.no_grad():
+    outputs = model(**inputs)
+
+answer_start_index = outputs.start_logits.argmax()
+answer_end_index = outputs.end_logits.argmax()
+predict_answer_token_ids = inputs.input_ids[0, answer_start_index : answer_end_index + 1]
+predict_answer_token = tokenizer.decode(predict_answer_token_ids)