Dynamic encodings

[pelikhan]

It's a loosing battle to try to handle all possible tokenizers. Instead learn them on the fly using logorobs.

• learn and cache encoding
• application to logit bias

[github-actions]

Task Analysis: Review an issue related to dynamic encodings in a larger context.

Issue Summary:
The title suggests that the issue revolves around handling different tokenizers dynamically. The body elaborates on trying to learn and cache encodings on-the-fly using some form of "logorobs," which seems not to be a standard word or commonly used term, possibly meant to represent some dynamic learning mechanism.

Feedback:
It's clear that the problem statement has a typo or unclear terminology ("loosing" should be "losing"). Additionally, the suggestion about using "logorobs" for learning and caching encodings, coupled with an incomplete task list, leaves the issue somewhat vague. Could you please clarify what is meant by "logorobs" and provide more details on how this approach fits into your solution? A proper description of the proposed method and its intended use within the broader context would be helpful for better understanding and implementation.

Suggestions:

• Correct spelling errors in the title and body ("loosing" should be "losing").
• Clarify or provide a definition for "logorobs."
• Flesh out the task list with more details on each item, including specific approaches, algorithms, or references to relevant literature.
• Include any relevant code snippets or pseudo-code to demonstrate existing implementations or propose new ones.

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