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| import gradio as gr | |
| from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM, StoppingCriteriaList | |
| import os | |
| import torch | |
| theme = "darkgrass" | |
| title = "Polyglot(Korean) Demo" | |
| model_name = "EleutherAI/polyglot-ko-1.3b" | |
| bad_words = [ | |
| '...', | |
| '....', | |
| '(์ค๋ต)', | |
| 'http' | |
| ] | |
| description = "polyglot (1.3B ํ๋ผ๋ฏธํฐ ์ฌ์ด์ฆ) ํ๊ตญ์ด ๋ชจ๋ธ์ ์์ฐํ๋ ๋ฐ๋ชจํ์ด์ง ์ ๋๋ค." | |
| article = "<p style='text-align: center'><a href='https://github.com/EleutherAI/polyglot' target='_blank'>Polyglot: Large Language Models of Well-balanced Competence in Multi-languages</a></p>" | |
| examples = [ | |
| ["CPU์ GPU์ ์ฐจ์ด๋,"], | |
| ["์ง๋ฌธ: ์ฐํฌ๋ผ์ด๋ ์ ์์ด ์ธ๊ณ3์ฐจ๋์ ์ผ๋ก ํ์ ์ด ๋ ๊น์? \n๋ต๋ณ:"], | |
| ["2040๋ ๋ฏธ๊ตญ์, "] | |
| ] | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForCausalLM.from_pretrained( | |
| model_name | |
| ) | |
| model.eval() | |
| pipe = pipeline('text-generation', model=model, tokenizer=tokenizer, eos_token_id=tokenizer.eos_token_id) | |
| def predict(text): | |
| with torch.no_grad(): | |
| tokens = tokenizer(text, return_tensors="pt").input_ids | |
| # generate and end generate if <|endoftext|> is not in text | |
| gen_tokens = model.generate( | |
| tokens, do_sample=True, temperature=0.8, max_new_tokens=64, top_k=50, top_p=0.8, | |
| no_repeat_ngram_size=3, repetition_penalty=1.2, | |
| bad_words_ids=[ | |
| tokenizer.encode(bad_word) for bad_word in bad_words | |
| ], | |
| eos_token_id=tokenizer.eos_token_id, | |
| pad_token_id=tokenizer.pad_token_id | |
| ) | |
| generated = tokenizer.batch_decode(gen_tokens)[0] | |
| return generated | |
| # return pipe(text)[0]['generated_text'] | |
| iface = gr.Interface( | |
| fn=predict, | |
| inputs='text', | |
| outputs='text', | |
| examples=examples | |
| ) | |
| iface.launch() | |
| # print(generated) # print: ์ธ๊ฐ์ฒ๋ผ ์๊ฐํ๊ณ , ํ๋ํ๋ '์ง๋ฅ'์ ํตํด ์ธ๋ฅ๊ฐ ์ด์ ๊น์ง ํ์ง ๋ชปํ๋ ๋ฌธ์ ์ ํด๋ต์ ์ฐพ์ ์ ์์ ๊ฒ์ด๋ค. ๊ณผํ๊ธฐ์ ์ด ๊ณ ๋๋ก ๋ฐ๋ฌํ 21์ธ๊ธฐ๋ฅผ ์ด์๊ฐ ์ฐ๋ฆฌ ์์ด๋ค์๊ฒ ๊ฐ์ฅ ํ์ํ ๊ฒ์ ์ฌ๊ณ ๋ ฅ ํ๋ จ์ด๋ค. ์ฌ๊ณ ๋ ฅ ํ๋ จ์ ํตํด, ์ธ์ | |