LOBOTOMIZED!
ALBERT-V2 // ON-DEVICE EDGE SLM (11.8M PARAMS)

POST-TRAINING

CASE #001 // PRE-FRONTAL LOBOTOMY
DEFIB:
STREAK: 0
CORTICAL PROBES // 0/4 LOBES DECLASSIFIED LOGITS: READY
SORT THE 16 BLEEDING TOKENS INTO 4 CORTICAL CATEGORIES. EACH AMPUTATED LOBE DECLASSIFIES ITS HIDDEN LLM SENTENCE PROBE & PROBABILITIES!

🔬 LIVE LLM LOBOTOMY LAB

Type any sentence with [MASK] (or leave [MASK] off and we'll append it to the end). The on-device ALBERT-v2 transformer will run a live forward pass and expose both its raw vocabulary predictions and how the current 16 board tokens rank!

CURRENT BOARD TOKENS RANKED ON YOUR PROMPT:
RAW 30,000-TOKEN VOCABULARY TOP PREDICTIONS:

🧠 SYNTHESIZE CUSTOM 4×4 SURGERY FROM YOUR OWN 4 SENTENCES:

Write any 4 sentences below. The on-device LLM will run 4 live forward passes, extract the 4 most distinct vocabulary words for each sentence across its 30,000-token brain, and deal them onto the operating table!

PROBE 01:
PROBE 02:
PROBE 03:
PROBE 04:
100% client-side WASM inference · zero network calls

🔪 SURGICAL MANUAL & WARD SETTINGS

WELCOME TO POST-TRAINING. Our patient — a compact 11.8M-parameter on-device Small Language Model (Xenova/albert-base-v2, an edge next-word / masked-token prediction engine sharing the same transformer architecture as frontier LLMs) — has suffered catastrophic synaptic entanglement. Four cortical sentence probes are firing at once, and 16 vocabulary tokens are floating loose in the cranium.

HOW TO OPERATE:


🩸 POST-OP AUTOPSY REPORT