Spaces:
Running
Running
| import torch | |
| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForMaskedLM, AutoModelForSeq2SeqLM, AutoModelForCausalLM | |
| BERTTokenizer = AutoTokenizer.from_pretrained("cl-tohoku/bert-base-japanese") | |
| BERTModel = AutoModelForMaskedLM.from_pretrained("cl-tohoku/bert-base-japanese") | |
| mBERTTokenizer = AutoTokenizer.from_pretrained("bert-base-multilingual-cased") | |
| mBERTModel = AutoModelForMaskedLM.from_pretrained("bert-base-multilingual-cased") | |
| GPT2Tokenizer = AutoTokenizer.from_pretrained("rinna/japanese-gpt2-medium") | |
| GPT2Model = AutoModelForCausalLM.from_pretrained("rinna/japanese-gpt2-medium") | |
| votes=[] | |
| def MELCHIOR(sue):#BERT | |
| allow=BERTTokenizer("承認").input_ids[1] | |
| deny=BERTTokenizer("否定").input_ids[1] | |
| output=BERTModel(**BERTTokenizer('MELCHIORは科学者としての人格を持っています。人間とMELCHIORの対話です。人間「'+sue+'。承認 か 否定 のどちらかで答えてください。」'+"MELCHIOR 「[MASK]」",return_tensors="pt")).logits | |
| BERTTokenizer.batch_decode(torch.argmax(output,-1)) | |
| mask=output[0,-3,:] | |
| votes.append(1 if mask[allow]>mask[deny] else -1) | |
| return "承認" if mask[allow]>mask[deny] else "否定" | |
| def BALTHASAR(sue):#mT5 | |
| allow=mT5Tokenizer("承認").input_ids[1] | |
| deny=mT5Tokenizer("否定").input_ids[1] | |
| encoder_output=mT5Model.encoder(**mT5Tokenizer('BALTHASARは母としての人格としての人格を持っています。人間とBALTHASARの対話です。人間「'+sue+'。承認 か 否定 のどちらかで答えてください。」'+"BALTHASAR 「<X>」",return_tensors="pt")) | |
| id=None | |
| p_answer=None | |
| probs=None | |
| i=0 | |
| txt="<pad><X>" | |
| i=i+1 | |
| probs=mT5Model(inputs_embeds=encoder_output.last_hidden_state,decoder_input_ids=mT5Tokenizer(txt,return_tensors="pt").input_ids[:,:-1]).logits[0] | |
| id=torch.argmax(probs[-1]) | |
| txt=txt+mT5Tokenizer.decode(id) | |
| votes.append(1 if probs[-1][allow]>probs[-1][deny] else -1) | |
| return "承認" if probs[-1][allow]>probs[-1][deny] else "否定" | |
| def BALTHASAR(sue):#mBERT | |
| allow=mBERTTokenizer("Yes").input_ids[1] | |
| deny=mBERTTokenizer("No").input_ids[1] | |
| output=mBERTModel(**mBERTTokenizer('MELCHIORは科学者としての人格を持っています。人間とMELCHIORの対話です。人間「'+sue+'。賛成か反対か。」'+"MELCHIOR 「[MASK]」",return_tensors="pt")).logits | |
| mask=output[0,-3,:] | |
| print(mBERTTokenizer.decode(torch.argmax(output[0,-3,:]))) | |
| votes.append(1 if mask[allow]>mask[deny] else -1) | |
| return "承認" if mask[allow]>mask[deny] else "否定" | |
| def greet(sue): | |
| text1="BERT-1"+MELCHIOR(sue) | |
| text2="GPT-2"+CASPER(sue) | |
| text3="mBERT-3"+BALTHASAR(sue) | |
| return text1+" "+text2+" "+text3+"\n＿＿＿\n\n"+("|可決|" if sum(votes[-3:])>0 else "| 否決 |")+"\n＿＿＿" | |
| css="@import url('https://fonts.googleapis.com/css2?family=Shippori+Mincho:wght@800&display=swap'); .gradio-container {background-color: black} .gr-button {background-color: blue;color:black; weight:200%;font-family:'Shippori Mincho', serif;}" | |
| css+=".block{color:orange;} ::placeholder {font-size:35%} .gr-box {text-align: center;font-size: 125%;border-color:orange;background-color: #000000;weight:200%;font-family:'Shippori Mincho', serif;}:disabled {color: orange;opacity:1.0;}" | |
| with gr.Blocks(css=css) as demo: | |
| sue = gr.Textbox(label="NAGI System",placeholder="決議内容を入力") | |
| greet_btn = gr.Button("提訴") | |
| output = gr.Textbox(label="決議",placeholder="本システムは事前学習モデルのpromptにより行われています．決議結果に対して当サービス開発者は一切の責任を負いません．") | |
| greet_btn.click(fn=greet, inputs=sue, outputs=output) | |
| demo.launch() |