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49 lines
954 B
Python
49 lines
954 B
Python
#!/usr/bin/env python
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# coding: utf-8
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# In[2]:
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# installing transformers
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# !pip install -q git+https://github.com/huggingface/transformers.git
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# !pip install -q tensorflow==2.1
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# In[12]:
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import tensorflow as tf
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from transformers import TFGPT2LMHeadModel, GPT2Tokenizer
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import gradio
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# In[4]:
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tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
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# add the EOS token as PAD token to avoid warnings
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model = TFGPT2LMHeadModel.from_pretrained("gpt2", pad_token_id=tokenizer.eos_token_id)
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# In[15]:
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def predict(inp):
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input_ids = tokenizer.encode(inp, return_tensors='tf')
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beam_output = model.generate(input_ids, max_length=49, num_beams=5, no_repeat_ngram_size=2, early_stopping=True)
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output = tokenizer.decode(beam_output[0], skip_special_tokens=True, clean_up_tokenization_spaces=True)
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return ".".join(output.split(".")[:-1]) + "."
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# In[18]:
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gradio.Interface(predict,"textbox","textbox").launch(inbrowser=True)
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# In[ ]:
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