22085081bb
Co-authored-by: Ying Sheng <sqy1415@gmail.com> Co-authored-by: Liangsheng Yin <hnyls2002@gmail.com> Co-authored-by: Zhiqiang Xie <xiezhq@stanford.edu> Co-authored-by: parasol-aser <3848358+parasol-aser@users.noreply.github.com> Co-authored-by: LiviaSun <33578456+ChuyueSun@users.noreply.github.com> Co-authored-by: Cody Yu <hao.yu.cody@gmail.com>
27 lines
772 B
Python
27 lines
772 B
Python
import json
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import transformers
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import wikipedia
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name = "meta-llama/Llama-2-7b-chat-hf"
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t = transformers.AutoTokenizer.from_pretrained(name)
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city_names = ["los angles", "london", "tokyo", "beijing", "singapore"]
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for city_name in city_names:
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content = str(wikipedia.page(city_name).content)
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content = content.replace("\n\n", "\n")
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tokens = t.encode(content)
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truncate_len = int((10000 / len(tokens)) * len(content))
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truncate_content = content[:truncate_len]
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truncate_tokens = t.encode(truncate_content)
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# Count token
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print(f"city_name: {city_name}, #tokens: {len(tokens)}, #truncate tokens: {len(truncate_tokens)}")
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with open("questions.jsonl", "a") as fout:
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fout.write(json.dumps({"document": truncate_content}) + "\n")
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