LLM Engineering course : Day 2 - 5
Open Source Vs Closed Source Model
See below , canvas is used for Coding along side with ChatGPT
Please note gap between words may come up as part of token , another example below
Rule of thumb is a token maps to 4 characters
Context Window
LLM appear to have a memory , what is really happening is everytime you talk to LLM / ChatGPT the entire conversation (including initial ques , its response, followup ques etc) are passed in again as a long prompt. To understand what is most likely to come next.
What is Context Window ?
https://www.ibm.com/think/topics/context-window
Comparing different context windows
https://medium.com/@genai.works/comprehensive-comparison-of-large-language-models-llms-0da7e894e419
Compare Models
- https://www.vellum.ai/llm-leaderboard
- https://www.youtube.com/watch?v=C8ftIfg6ROs&t=390s
- context window, cost per million input token, cost per million output window
- gemini has context window of 1million token = 750k words = entire work of shakespear
What is one shot prompting ?
In the prompt we send the model, we give one example of what we looking for, the kind of thing we expecting it to reply.
Multi shot prompting = tell what to respond in different situations
- https://www.ibm.com/think/topics/one-shot-prompting
- https://anilktalla.medium.com/prompt-engineering-1-shot-prompting-283a0b2b1467
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