Handling Token Limit Issues in Llama 3.2:3b-Instruct Model (2048 Tokens Max)

[pandiyan90]

I'm using the Llama 3.2:3b-instruct model and encountered the following error: 'This model's maximum context length is 2048 tokens. However, you requested 2049 tokens (1681 in the messages, 368 in the completion).' I understand this is due to exceeding the token limit, but I'd like to know:

Why does this token limit exist, and is there a technical reason for this specific constraint?
Are there any best practices or techniques for reducing token usage without losing critical context in messages or completions?

Is there an official document or update from the developers regarding this token limit or potential plans to increase it in future versions?
Are there alternative strategies (e.g., chunking, summarization, or other tricks) that others have used effectively with this model in similar scenarios?

Any insights, guidance, or links to documentation would be greatly appreciated!