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README.md
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@@ -5,4 +5,22 @@ language:
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base_model:
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- GroNLP/gpt2-small-italian
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pipeline_tag: text-generation
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---
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base_model:
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- GroNLP/gpt2-small-italian
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pipeline_tag: text-generation
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---
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```
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("VerbACxSS/sempl-it-gpt2-small-italian", model_max_length=1024)
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model = AutoModelForCausalLM.from_pretrained("VerbACxSS/sempl-it-gpt2-small-italian")
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model.eval()
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text_to_simplify = 'Nella fattispecie, questo documento è di natura prescrittiva'
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prompt = f'### [Input]:\n{text_to_simplify}\n\n###[Output]:\n'
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x = tokenizer(prompt, max_length=1024, truncation=True, padding=True, return_tensors='pt').input_ids
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y = model.generate(x, max_length=1024)[0]
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y_dec = tokenizer.decode(y, max_length=1024, truncation=True)
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output = y_dec.split('###[Output]:\n')[1].split('<|endoftext|>')[0].strip()
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print(output)
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```
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