Pre-training is a foundational phase in developing language models, especially large language models (LLMs). This initial step equips the model with a broad understanding of language, including its structure (syntax) and meaning (semantics). By the end of pre-training, the model acts as a generalist, ready to be fine-tuned for specific tasks or domains.
Pre-training involves exposing a language model to vast amounts of text—often more than a trillion words. These datasets may include:
Through this process, the model develops a deep understanding of:
For example, the model learns that “The cat sat on the mat” is both grammatically correct and makes sense in English.
Pre-training gives the model a general “education,” much like earning a general studies degree at a university. However, the model hasn’t yet specialized in any specific domain or task.
Specialization happens in later phases, often referred to as:
Pre-training lays the groundwork for everything a language model can do, making it:
After pre-training, language models can be fine-tuned for tasks like:
Pre-training is the critical first step in developing intelligent, adaptable language models. By understanding this process, businesses can better leverage AI for innovative and impactful applications.
Contact Launch to learn how pre-training and fine-tuning can bring cutting-edge AI solutions to your organization.
Pre-training is a foundational phase in developing language models, especially large language models (LLMs). This initial step equips the model with a broad understanding of language, including its structure (syntax) and meaning (semantics). By the end of pre-training, the model acts as a generalist, ready to be fine-tuned for specific tasks or domains.
Pre-training involves exposing a language model to vast amounts of text—often more than a trillion words. These datasets may include:
Through this process, the model develops a deep understanding of:
For example, the model learns that “The cat sat on the mat” is both grammatically correct and makes sense in English.
Pre-training gives the model a general “education,” much like earning a general studies degree at a university. However, the model hasn’t yet specialized in any specific domain or task.
Specialization happens in later phases, often referred to as:
Pre-training lays the groundwork for everything a language model can do, making it:
After pre-training, language models can be fine-tuned for tasks like:
Pre-training is the critical first step in developing intelligent, adaptable language models. By understanding this process, businesses can better leverage AI for innovative and impactful applications.
Contact Launch to learn how pre-training and fine-tuning can bring cutting-edge AI solutions to your organization.