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SVLM, is designed to answer questions based on research papers from the ACL dataset. It leverages the BART architecture to generate precise answers from scientific abstracts.1from transformers import AutoTokenizer, TFAutoModelForSeq2SeqLM
2
3# Load the model and tokenizer
4tokenizer = AutoTokenizer.from_pretrained("Binarybardakshat/SVLM")
5model = TFAutoModelForSeq2SeqLM.from_pretrained("Binarybardakshat/SVLM")
6
7# Example input
8input_text = "What is the main contribution of the paper titled 'Your Paper Title'?"
9
10# Tokenize input
11inputs = tokenizer(input_text, return_tensors="tf", padding=True, truncation=True)
12
13# Generate answer
14outputs = model.generate(inputs.input_ids, max_length=50, num_beams=5, early_stopping=True)
15answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
16
17print("Answer:", answer)