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--- |
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license: apache-2.0 |
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pipeline_tag: question-answering |
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--- |
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### How to use |
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```python |
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from transformers import T5Tokenizer, T5ForConditionalGeneration |
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model_name = "KhantKyaw/T5-small_new_chatbot" |
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tokenizer = T5Tokenizer.from_pretrained(model_name) |
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model = T5ForConditionalGeneration.from_pretrained(model_name) |
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def generate_response(input_text): |
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input_ids = tokenizer.encode(input_text, return_tensors='pt') |
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outputs = model.generate(input_ids, |
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min_length=5, |
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max_length=300, |
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do_sample=True, num_beams=5, no_repeat_ngram_size=2) |
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generated_text = tokenizer.decode( |
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outputs[0], skip_special_tokens=True) |
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return generated_text |
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generate_response("how to be healthy?") |
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``` |
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Contributors: |
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Team Machina: Khant Kyaw, Hein Min Htun, Htet Myat Noe Aung, Thant Zin Oo |
