Introduction to Large Language Models
2025/2026 Exam Questions Marking
Scheme New Update | A+ Rated
large language models - 🧠ANSWER ✔✔large, general-purpose language
models can be pre-trained (basic common language problems: text
classification, question answering, document summarization, text
generation) and then fine-tuned (specific problems in different fields)
specific purposes
3 major features of large language models - 🧠ANSWER ✔✔1. large:
-large training dataset
- a large number of parameters: memory and knowledge machine-learned
from training, define the skills of the model
2. general purpose: model sufficient ability to solve a common problem
-commonality of human languages
-resource restriction
COPYRIGHT©JOSHCLAY 2025/2026. YEAR PUBLISHED 2025. COMPANY REGISTRATION NUMBER: 619652435. TERMS OF USE. PRIVACY
STATEMENT. ALL RIGHTS RESERVED
1
, 3. pre-trained and fine-tuned
benefits of using large language models - 🧠ANSWER ✔✔1. a single code
can be used for different tasks
2. the fine-tuning process requires minimal field data
-obtain decent performance even with minimal training
-can be used for few-shot or even zero-shot scenarios
3. the performance of LLM is continuously growing when you add more
data and parameters
few-shot - 🧠ANSWER ✔✔in machine learning, it refers to training a model
with minimal data
zero-shot - 🧠ANSWER ✔✔in Machine learning, implies that a model can
recognize things that have not explicitly been taught in the training before
Pathways Language Model (PaLM) - 🧠ANSWER ✔✔-has 540 billion
parameters
COPYRIGHT©JOSHCLAY 2025/2026. YEAR PUBLISHED 2025. COMPANY REGISTRATION NUMBER: 619652435. TERMS OF USE. PRIVACY
STATEMENT. ALL RIGHTS RESERVED
2
2025/2026 Exam Questions Marking
Scheme New Update | A+ Rated
large language models - 🧠ANSWER ✔✔large, general-purpose language
models can be pre-trained (basic common language problems: text
classification, question answering, document summarization, text
generation) and then fine-tuned (specific problems in different fields)
specific purposes
3 major features of large language models - 🧠ANSWER ✔✔1. large:
-large training dataset
- a large number of parameters: memory and knowledge machine-learned
from training, define the skills of the model
2. general purpose: model sufficient ability to solve a common problem
-commonality of human languages
-resource restriction
COPYRIGHT©JOSHCLAY 2025/2026. YEAR PUBLISHED 2025. COMPANY REGISTRATION NUMBER: 619652435. TERMS OF USE. PRIVACY
STATEMENT. ALL RIGHTS RESERVED
1
, 3. pre-trained and fine-tuned
benefits of using large language models - 🧠ANSWER ✔✔1. a single code
can be used for different tasks
2. the fine-tuning process requires minimal field data
-obtain decent performance even with minimal training
-can be used for few-shot or even zero-shot scenarios
3. the performance of LLM is continuously growing when you add more
data and parameters
few-shot - 🧠ANSWER ✔✔in machine learning, it refers to training a model
with minimal data
zero-shot - 🧠ANSWER ✔✔in Machine learning, implies that a model can
recognize things that have not explicitly been taught in the training before
Pathways Language Model (PaLM) - 🧠ANSWER ✔✔-has 540 billion
parameters
COPYRIGHT©JOSHCLAY 2025/2026. YEAR PUBLISHED 2025. COMPANY REGISTRATION NUMBER: 619652435. TERMS OF USE. PRIVACY
STATEMENT. ALL RIGHTS RESERVED
2
