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--- |
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license: mit |
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widget: |
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- text: |- |
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<SC1>- как ты? |
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- <extra_id_0> |
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example_title: how r u |
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language: |
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- ru |
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pipeline_tag: text2text-generation |
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--- |
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# Usage |
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```python |
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import torch |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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device='cuda' |
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tokenizer = AutoTokenizer.from_pretrained('TeraSpace/dialofred') |
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model = AutoModelForSeq2SeqLM.from_pretrained('TeraSpace/dialofred').to(device) |
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while True: |
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text_inp = input("=>") |
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lm_text=f'<SC1>- {text_inp}\n- <extra_id_0>' |
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input_ids=torch.tensor([tokenizer.encode(lm_text)]).to(device) |
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# outputs=model.generate(input_ids=input_ids, |
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# max_length=200, |
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# eos_token_id=tokenizer.eos_token_id, |
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# early_stopping=True, |
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# do_sample=True, |
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# temperature=1.0, |
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# top_k=0, |
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# top_p=0.85) |
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# outputs=model.generate(input_ids,eos_token_id=tokenizer.eos_token_id,early_stopping=True) |
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outputs=model.generate(input_ids=input_ids, |
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max_length=200, |
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eos_token_id=tokenizer.eos_token_id, |
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early_stopping=True, |
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do_sample=True, |
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temperature=0.7, |
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top_k=0, |
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top_p=0.8) |
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print(tokenizer.decode(outputs[0][1:])) |
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``` |
