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--- |
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license: gpl-3.0 |
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datasets: |
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- multi_woz_v22 |
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language: |
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- en |
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metrics: |
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- bleu |
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- rouge |
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--- |
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Pretrained model: [GODEL-v1_1-base-seq2seq](https://huggingface.co/microsoft/GODEL-v1_1-base-seq2seq/) |
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Fine-tuning dataset: [MultiWOZ 2.2](https://github.com/budzianowski/multiwoz/tree/master/data/MultiWOZ_2.2) |
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# How to use: |
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```python |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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# Load tokenizer and model |
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tokenizer = AutoTokenizer.from_pretrained("gonced8/godel-multiwoz") |
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model = AutoModelForSeq2SeqLM.from_pretrained("gonced8/godel-multiwoz") |
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# Encoder input |
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context = [ |
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"USER: I need train reservations from norwich to cambridge", |
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"SYSTEM: I have 133 trains matching your request. Is there a specific day and time you would like to travel?", |
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"USER: I'd like to leave on Monday and arrive by 18:00.", |
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] |
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input_text = " EOS ".join(context[-5:]) + " => " |
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model_inputs = tokenizer( |
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input_text, max_length=512, truncation=True, return_tensors="pt" |
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)["input_ids"] |
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# Decoder input |
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answer_start = "SYSTEM: " |
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decoder_input_ids = tokenizer( |
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"<pad>" + answer_start, |
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max_length=256, |
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truncation=True, |
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add_special_tokens=False, |
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return_tensors="pt", |
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)["input_ids"] |
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# Generate |
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output = model.generate( |
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model_inputs, decoder_input_ids=decoder_input_ids, max_length=256 |
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) |
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output = tokenizer.decode( |
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output[0], clean_up_tokenization_spaces=True, skip_special_tokens=True |
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) |
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print(output) |
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# SYSTEM: TR4634 arrives at 17:35. Would you like me to book that for you? |
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``` |
