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1pink-elephant-llm-14b (dense 14B)
2 └─add weights / upcycle──▶ 48b-moe-base (8-expert MoE) ──train──▶ 48b
3 └─remaining epochs──▶ 48b-s (flagship, s = smarter)
4 └─+SFT best (step90000)──▶ +DPO best (dpo-best)──▶ FINAL MODEL ⇐ verified here
5 └─GGUF conversion──▶ run locally via Ollama / LM Studiobase → moe → train → sft → dpo → verification (this) → release| Path | Purpose |
|---|---|
tooling/structural/verify_architecture.py | S1. Verifies the released model's config, parameter scale, and full base_model: lineage chain against the architectural contract. CPU-only, CI-runnable. |
tooling/structural/verify_weights.py | S2. Verifies SFT + DPO LoRA adapters are shape-consistent with the base (hidden/intermediate/expert dims) so they merge cleanly. CPU-only. |
tooling/adapter_to_peft.py | Converts the pipeline's custom .pt LoRA adapters (SFT sft-lora-step*.pt, DPO dpo-lora-step*.pt) into standard PEFT dirs that PeftModel.from_pretrained consumes. |
tooling/run_benchmarks.py | S3–S6. Loads base 48B-S + merges SFT best + DPO best, then runs GSM8K + MMLU. Shell-friendly alternative to the notebook. |
tooling/smoke_test.py | S4. Minimal generation sanity check of the final model. |
tooling/benchmarks/gsm8k.py | Raw GSM8K evaluation script (batch, checkpointed — used in the live run). |
tooling/benchmarks/mmlu_5shot.py | Raw 5-shot MMLU script (balanced stratified sampling — used in the live run). |
tooling/benchmarks/mmlu_chunk.py | Chunked MMLU runner (progress-safe for long runs). |
tooling/run_all.py | Orchestrates the CPU-side checks (structural + weights) in one command. |
notebooks/verify_full_model.py | Single notebook running all six stages (S1–S6) on one Blackwell host. |
results/ | Recorded verification outputs (JSON). |
report/ALIGNED_VERIFICATION_REPORT.pdf | This verification report (print-ready). |
requirements.txt | GPU-benchmark dependencies. |
1pip install -r requirements.txt # torch optional for S1, needed for adapter inspection
2python tooling/run_all.py --structural \
3 --sft /path/sft-lora-step90000.pt --dpo /path/dpo-best.pt \
4 --json results/1# On the verification host:
2python tooling/adapter_to_peft.py sft-lora-step90000.pt peft/sft
3python tooling/adapter_to_peft.py dpo-best.pt peft/dpo
4python tooling/run_benchmarks.py # GSM8K + MMLU (S3–S6)
5# or run notebooks/verify_full_model.py (single notebook, all of S1–S6)Populated from live verification runs on our Blackwell host. Seeresults/JSON files.
| Benchmark | Result | Detail |
|---|---|---|
| GSM8K (math reasoning) | 68.5% | 61/89 on a random sample; answer is extraction |
| MMLU (knowledge, 5-shot) | 60.0% | 24/40 balanced across 7 subjects; letter extraction |
| Structural contract | PASS | 16/16 checks (config, params, lineage) |
![]() Headline benchmarks: GSM8K 68.5% · MMLU 60.0% | ![]() MMLU (5-shot) accuracy by subject | |
![]() Structural pre-release gate: 16/16 | ![]() Verification stages across the whole final model |
bf16.pinkelephantlimited/pinkelephant-llm-48b-s. Adapters:
pinkelephantlimited/pinkelephant-llm-48b-s-dpo (sft/sft-lora-step90000.pt,
dpo/dpo-best.pt).