Training method and apparatus for full atomic structure prediction model, and electronic device
AssigneeBeijing Baidu Netcom Science Technology Co., Ltd.
InventorsZhongjun He, Hua Wu, Haifeng Wang
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Abstract
An information processing method. The method includes obtaining a first bilingual sentence pair, in which the first bilingual sentence pair comprises a source language sentence and a target language sentence; and obtaining a distilled second bilingual sentence pair by distilling a first language sentence in the first bilingual sentence pair based on a large language model (LLM), in which the first language sentence is the source language sentence or the target language sentence.
Claims20
An information processing method, comprising:
- obtaining a first bilingual sentence pair, wherein the first bilingual sentence pair comprises a source language sentence and a target language sentence;
- and
- obtaining a distilled second bilingual sentence pair by distilling a first language sentence in the first bilingual sentence pair based on a large language model (LLM), wherein the first language sentence is the source language sentence or the target language sentence.
An electronic device comprising:
- at least one processor;
- and
- a memory communicatively coupled to the at least one processor;
- wherein,
- the memory stores instructions executable by the at least one processor, when the instructions are executed by the at least one processor, the at least one processor is configured to:
- obtain a first bilingual sentence pair, wherein the first bilingual sentence pair comprises a source language sentence and a target language sentence;
- and
- obtain a distilled second bilingual sentence pair by distilling a first language sentence in the first bilingual sentence pair based on a large language model (LLM), wherein the first language sentence is the source language sentence or the target language sentence.
A non-transitory computer-readable storage medium having computer instructions stored thereon, wherein the computer instructions are configured to enable a computer to implement the method comprising:
- obtaining a first bilingual sentence pair, wherein the first bilingual sentence pair comprises a source language sentence and a target language sentence;
- and
- obtaining a distilled second bilingual sentence pair by distilling a first language sentence in the first bilingual sentence pair based on a large language model (LLM), wherein the first language sentence is the source language sentence or the target language sentence.
Dependencies are inferred from the claim text.