26 lines
950 B
Python
26 lines
950 B
Python
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import pickle
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from transformers import AutoTokenizer, AutoModel, T5ForConditionalGeneration
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from tqdm import tqdm
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from config import LABELS_LIST
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device = 'cuda'
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model_path= 't5-retrained/checkpoint-110000'
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from transformers import AutoModelForSequenceClassification
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model = T5ForConditionalGeneration.from_pretrained(model_path).cuda()
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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for dataset in ('dev-0', 'test-A'):
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with open(f'../{dataset}/in.tsv') as f_in, open(f'../{dataset}/out.tsv','w') as f_out:
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for line_in in tqdm(f_in, total=150_000):
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_,_, text = line_in.split('\t')
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text = text.rstrip('\n')
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inputs = tokenizer(text, padding=True, truncation=True, return_tensors="pt").input_ids.to(device)
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outputs = model.generate(inputs)
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o = tokenizer.decode(outputs[0], skip_special_tokens=True)
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o = LABELS_LIST[int(o)]
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f_out.write(o + '\n')
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