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1
2 !pip install transformers sentencepiece
3
4 from transformers import MT5ForConditionalGeneration, AutoTokenizer
5 # Load the trained model
6 model = MT5ForConditionalGeneration.from_pretrained("Chhabi/mt5-small-finetuned-Nepali-Health-50k-2")
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8 # Load the tokenizer for generating new output
9 tokenizer = AutoTokenizer.from_pretrained("Chhabi/mt5-small-finetuned-Nepali-Health-50k-2",use_fast=True)
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13 query = "म धेरै थकित महसुस गर्छु र मेरो नाक बगिरहेको छ। साथै, मलाई घाँटी दुखेको छ र अलि टाउको दुखेको छ। मलाई के भइरहेको छ?"
14 input_text = f"answer: {query}"
15 inputs = tokenizer(input_text,return_tensors='pt',max_length=256,truncation=True).to("cuda")
16 print(inputs)
17 generated_text = model.generate(**inputs,max_length=512,min_length=256,length_penalty=3.0,num_beams=10,top_p=0.95,top_k=100,do_sample=True,temperature=0.7,num_return_sequences=3,no_repeat_ngram_size=4)
18 print(generated_text)
19 # generated_text
20 generated_response = tokenizer.batch_decode(generated_text,skip_special_tokens=True)[0]
21 tokens = generated_response.split(" ")
22 filtered_tokens = [token for token in tokens if not token.startswith("<extra_id_")]
23 print(' '.join(filtered_tokens))
24