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import pandas as pd |
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import os |
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import torch |
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from transformers import T5Tokenizer, T5ForConditionalGeneration |
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from transformers.optimization import Adafactor |
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import time |
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import warnings |
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warnings.filterwarnings('ignore') |
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tokenizer = T5Tokenizer.from_pretrained('Sachinkelenjaguri/sa_T5_Table_to_text') |
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model = T5ForConditionalGeneration.from_pretrained('Sachinkelenjaguri/sa_T5_Table_to_text', return_dict=True) |
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#moving the model to device(GPU/CPU) |
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def generate(text): |
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model.eval() |
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input_ids = tokenizer.encode("WebNLG:{} </s>".format(text), return_tensors="pt") # Batch size 1 |
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# input_ids.to(dev) |
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s = time.time() |
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outputs = model.generate(input_ids) |
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gen_text=tokenizer.decode(outputs[0]).replace('<pad>','').replace('</s>','') |
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elapsed = time.time() - s |
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print('Generated in {} seconds'.format(str(elapsed)[:4])) |
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return gen_text |
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generate(' Russia | leader | Putin') |