Instructions to use Falln87/clerk-memory with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Falln87/clerk-memory with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Commit History
-
CLERK paper draft v0.1: method, benchmark spec, protocol; results tables pending observed runs
Verified signature76a8e7d -
CLERK project README: method summary, novelty statement, repro instructions
Verified signature7aab365 -
CLERK end-to-end reproducible pipeline (CPU smoke tests -> data -> LoRA SFT -> both evals)
Verified signature1c428b7 -
eval_locomo: fix choice_logprobs continuation scoring
Verified signature920a0c6 -
eval_locomo: clean rewrite (working choice log-likelihood scorer, consistent templates, single model loader)
Verified signature705d9d4 -
CLERK LoCoMo-MC10 zero-shot eval: incremental ledger build over LoCoMo sessions, MC log-likelihood scoring, full-context + prompted-ledger + summary-RAG baselines
Verified signatureca30e35 -
generator: fix gold_ops_for_events double-application bug; single-state implementation
Verified signature1d30dff -
tests_smoke: clean rewrite of invariant checks (gold ops executable, budget, round-trip, QA consistency)
Verified signature76e7c09 -
eval_synthetic: initialize stale-error counters in Runner.__init__
Verified signaturec88c20f -
CLERK pinned dependencies
Verified signature79f4cda -
CLERK smoke tests: gold ops executable, ledger round-trip, budget enforcement, QA supervision consistency
Verified signature415817c -
eval_synthetic: full clean rewrite (consistent generate contract, main, serialization helper)
Verified signaturef8cde5f -
CLERK synthetic eval: clerk rollout + prompted-ledger/full-context/sliding-window/RAG baselines, per-type accuracy, memory-state metrics, token costs
Verified signature193e1ae -
train_sft: honor --base-model and --max-length, drop unused import
Verified signature6380390 -
CLERK LoRA SFT trainer (TRL SFTTrainer), verified against trl examples/sft_qlora; pushes adapter to the Hub
Verified signature4d8daa4 -
CLERK SFT dataset builder: timelines -> messages JSONL (CONSOLIDATE + ANSWER mixture), seeded shuffle
Verified signaturec498706 -
CLERK shared prompt definitions (train/eval must never drift)
Verified signature865342a -
generator: temporal answer uses slot-held value; gold ADD evicts first when ledger full; budget default 12 for eviction pressure
Verified signature9dae931 -
generator: remove module-global session index; question targets restricted to ledger-supported predicates
Verified signature61cccdd -
common.py: fix facts_of valid_only semantics
Verified signaturea042d28 -
CLERK generator: correct single-pass timeline builder, ledger-aware question targets, eviction-safe gold ops
Verified signatured03cb0b -
CLERK generator: clean full rewrite of render_session and persona timeline builder
Verified signature3cd7b4e -
CLERK synthetic evolving-session generator: personas, updates/supersessions/tombstones, gold ledger transitions, seeded
Verified signaturefdcd0a4 -
CLERK core: slot schema, edit-op schema, deterministic reducer, serializers
Verified signature4f70a26 -
initial commit
Verified signature36958cf