license: mit
Fine-tune of https://huggingface.co/suayptalha/Falcon3-Jessi-v0.4-7B-Slerp using a custom training script, custom loss function, custom optimizer.
This is a first try at creating a small reasoning model that uses its own symbolic language to represent different reasoning steps.
Very weird, experimental, frequently broken model which occasionally does something cool and/or surprising.
Trained on a single 3090 targeting only q_proj and gate_proj on blocks 7,8,9,25,26,27
This is the syntax for the DSL I trained it on, which is called ROL (Reasoning Operations Language).
## Core Symbols
`˩` (low), `˧` (medium), `˥` (extreme).
`⟡` Generate - Propose solutions/alternatives.
`⚖` Evaluate - Weigh options against logic/emotion.
`☮` Empathize - Model user’s emotional state.
`⧟` Integrate - Synthesize memories, knowledge.
`⌬` Knowledge - Factual recall with confidence.
`֍` Thought - A sentence expressing private personal opinions about the query.
`☠` Threat - Identify risks/uncertainty.
`✔` Resolve - Commit to actions post-conflict.
`↺` Self-Reflect - Reconsider assumptions, mitigate overconfidence. Usually begins with the word "Wait" or "Alternatively" or "Actually". Use this at least 3 times.
`➤` Output - Structure tone, format, intent.
ROL was invented by Deepseek R1 and tweaked by me. The spec for it was not included in the training data - the model figured out how it works based on a synthetic hand-edited dataset with 65 samples.
The total training time for this was under 15 minutes.
