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README.md
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- KTDSbaseLM v0.11μ μ΄ 3.6GB ν¬κΈ°μ λ°μ΄ν°λ₯Ό λ°νμΌλ‘ νμ΅λμμ΅λλ€. μ΄ 233λ§ κ±΄μ QnA λ°μ΄ν°λ₯Ό ν¬ν¨νλ©°,
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κ·Έ μ€ 133λ§ κ±΄μ 135κ° μμμ κ°κ΄μ λ¬Έμ λ‘ κ΅¬μ±λμμ΅λλ€. μ΄ μμμλ νκ΅μ¬, μ¬ν, μ¬λ¬΄, λ²λ₯ , μΈλ¬΄, μν, μλ¬Ό, 물리, νν λ±μ΄ ν¬ν¨λλ©°,
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Chain of Thought λ°©μμΌλ‘ νμ΅λμμ΅λλ€. λν 130λ§ κ±΄μ μ£Όκ΄μ λ¬Έμ λ νκ΅μ¬, μ¬λ¬΄, λ²λ₯ , μΈλ¬΄, μν λ± 100κ° μμμ κ±Έμ³ νμ΅λμμ΅λλ€.
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βΈ μ¬μ© μ¬λ‘
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νΈν₯λ λ°μ΄ν°κ° ν¬ν¨λ κ²½μ° νΈν₯λ μλ΅μ΄ μμ±λ κ°λ₯μ±λ μ‘΄μ¬ν©λλ€.
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βΊ μ¬μ© λ°©λ²
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from transformers import AutoModel, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained("
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model = AutoModel.from_pretrained("
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inputs = tokenizer("μλ
νμΈμ", return_tensors="pt")
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outputs = model(**inputs)
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- KTDSbaseLM v0.11μ μ΄ 3.6GB ν¬κΈ°μ λ°μ΄ν°λ₯Ό λ°νμΌλ‘ νμ΅λμμ΅λλ€. μ΄ 233λ§ κ±΄μ QnA λ°μ΄ν°λ₯Ό ν¬ν¨νλ©°,
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κ·Έ μ€ 133λ§ κ±΄μ 135κ° μμμ κ°κ΄μ λ¬Έμ λ‘ κ΅¬μ±λμμ΅λλ€. μ΄ μμμλ νκ΅μ¬, μ¬ν, μ¬λ¬΄, λ²λ₯ , μΈλ¬΄, μν, μλ¬Ό, 물리, νν λ±μ΄ ν¬ν¨λλ©°,
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Chain of Thought λ°©μμΌλ‘ νμ΅λμμ΅λλ€. λν 130λ§ κ±΄μ μ£Όκ΄μ λ¬Έμ λ νκ΅μ¬, μ¬λ¬΄, λ²λ₯ , μΈλ¬΄, μν λ± 100κ° μμμ κ±Έμ³ νμ΅λμμ΅λλ€.
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- νμ΅ Instruction Format
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{"prompt": "<prompt text>", "completion": "<ideal generated text>"}
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{"prompt": "<prompt text>", "completion": "<ideal generated text>"}
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{"prompt": "<prompt text>", "completion": "<ideal generated text>"}
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βΈ μ¬μ© μ¬λ‘
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νΈν₯λ λ°μ΄ν°κ° ν¬ν¨λ κ²½μ° νΈν₯λ μλ΅μ΄ μμ±λ κ°λ₯μ±λ μ‘΄μ¬ν©λλ€.
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βΊ μ¬μ© λ°©λ²
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>> from transformers import AutoModel, AutoTokenizer
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>> tokenizer = AutoTokenizer.from_pretrained("")
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>> model = AutoModel.from_pretrained("")
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>> inputs = tokenizer("μλ
νμΈμ", return_tensors="pt")
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>> outputs = model(**inputs)
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>>
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