Merged checkpoint of the DeepLightning v4 fullrun LoRA trained on
nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16 (NeMo Automodel, corrected v4 config,
r=16 / alpha=32, two repeated MTP layers, dataset 19,573 rows, one epoch = 2,447 steps,
LR=2e-5, sequence length=4096, GBS/LBS=8/1, seed=1111, final adapter at epoch_0_step_2446).
The LoRA was merged into the base weights (architecture-aware merge preserving MTP tensors) so this
repo is a standalone dense BF16 model — no PEFT adapter needed at inference.
Architecture
Nemotron-H hybrid: Mamba + MoE + repeated MTP layers (GB10 / DGX Spark class). Query the model with
vLLM + --mamba-backend flashinfer for correct Mamba kernel dispatch. MTP tensors verified present (6513 keys, 270 MTP keys).
sixcat (limit=20, ~180 items), minus tools (harness expects OpenAI tool-call
JSON; this Hermes-trained model emits Hermes-XML <tool_call> blocks — a
wire-format mismatch, not a capability gap):
*tools/agentic parse failures are a harness wire-format artifact (Hermes-XML vs
OpenAI JSON), not a model defect. The model selects the correct tool and args.
Comparison vs stock baseline (v040-stock.json, same sixcat v0.4.0 identity): +4.17 overall (52.5 → 56.67). All categories at or above stock (K+15, M+5, T=0, I+5, C=0 ceiling, T=0 floor).
Note: Parallel NVFP4 quantization (lightning_w4a16_nvfp4_4o6 Four-Over-Six recipe) is in progress on the same merge. Accepted NVFP4 will be uploaded to vcruz305/DeepNemotron-3.5-Lightning-NVFP4 only after Gate 5 passes. This repo contains the BF16 merge only.
Training details (corrected v4 fullrun): 19,573-row dataset (SHA-256 verified), one shuffled epoch = 2,447 steps, LR=2e-5, LoRA rank/alpha=16/32, sequence length=4096, GBS/LBS=8/1, seed=1111, two repeated MTP layers, checkpoint every 250 steps, recovery retention latest two checkpoints. Final adapter epoch_0_step_2446.
See the full plan at the source workspace for Phase 0–5 gates, official lightning_w4a16_nvfp4_4o6 recipe, layer policy (MoE experts W4A16 NVFP4 Four-Over-Six, Mamba FP8, Attention BF16, KV FP8), and success criteria (≥98–99% recovery of BF16 agentic metrics).
