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--- |
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library_name: transformers |
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license: apache-2.0 |
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language: |
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- en |
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- ko |
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base_model: |
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- numind/NuExtract-1.5 |
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tags: |
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- llama-factory |
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--- |
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# Automatic Schema Induction(text-to-schema) Model |
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This model is a sub-task of text-to-json task that generates a JSON template given a text. |
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# Usage |
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```python |
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import json |
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import torch |
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from transformers import AutoModel, AutoTokenizer |
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model_name = "chnaaam/luSI-v1.0" |
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if torch.cuda.is_available(): |
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device = "cuda" |
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elif torch.backends.mps.is_available(): |
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device = "mps" |
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else: |
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device = "cpu" |
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model = AutoModel.from_pretrained(model_name, torch_dtype=torch.bfloat16, trust_remote_code=True).to(device).eval() |
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tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True) |
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text = """์์ด์ (IU, ๋ณธ๋ช
: ์ด์ง์, ๆ็ฅๆฉ[1], 1993๋
5์ 16์ผ~)๋ ๋ํ๋ฏผ๊ตญ์ ์ฑ์ด์ก๋ผ์ดํฐ, ์๊ณก๊ฐ, ๋ฐฐ์ฐ์ด๋ค. 2007๋
๋ก์ ์ํฐํ
์ธ๋จผํธ(ํ ์นด์นด์ค ์ํฐํ
์ธ๋จผํธ) ์ฐ์ต์์ผ๋ก ์ ์ ๊ณ์ฝ์ ๋งบ๊ณ 15์ธ์ ๋์ด์ 2008๋
์ฒซ EP์ธ ๋ก์คํธ ์ค ํ์ด๋(Lost and Found)๋ฅผ ํตํด ๊ฐ์๋ก ๋ฐ๋ทํ๋ค.""" |
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messages = [ |
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{"role": "user", "content": text} |
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] |
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text = tokenizer.apply_chat_template( |
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messages, |
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tokenize=False, |
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add_generation_prompt=True |
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) |
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device) |
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generated_ids = model.generate( |
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**model_inputs, |
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max_new_tokens=1024, |
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temperature=0.0 |
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) |
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generated_ids = [ |
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) |
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] |
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] |
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json_template = json.loads(response) |
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print(json_template) |
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``` |
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## Output |
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```json |
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{ |
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'Person': { |
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'Name': '', |
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'Stage name': '', |
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'Real name': '', |
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'Birth date': '', |
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'Nationality': '', |
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'Occupations': [], |
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'Debut': { |
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'Age': '', |
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'Year': '', |
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'Company': '', |
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'Contract type': '', |
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'EP': '', |
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'EP title': '' |
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} |
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} |
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} |
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``` |