DeepSeek-V4.1-Flash UNCENSORED — Engram tables, pre-packed for 4× DGX Spark (TP=4)

What is this? DeepSeek-V4.1-Flash carries two giant lookup tables the architecture calls Engram (at layers 1 and 14): ~189 GiB of n-gram-conditioned embeddings the model reads with a hash lookup on every token, in both prefill and decode. They are the reason the checkpoint is 510 GB but only ~305 GiB is "weights" — the tables are data, not matrix weights: never quantized, never sharded by tensor shape, never computed on. On a DGX Spark that distinction is life-or-death: host RAM is the GPU's memory (121.7 GiB unified per node). Park 189 GiB of tables in GPU memory and nothing fits; put them on NVMe and read rows directly (the kit's Engram row-store, with OFFLOAD_MODE=nvme), and a 4-node Spark fleet serves the full frontier model with room for a 1M-token context on top.

These are those tables, already packed into each rank's NVMe-resident binary shards — the output of Mia's pack_engram.py (the slow, all-read step you'd otherwise run once per node). Download → drop in → boot.

Packed from the abliterated checkpoint dealignai/DeepSeek-V4.1-Flash-UNCENSORED-FP8 with Mia AI Lab's 4×-Spark kit (SGLang, TP=4, EP=4, RoCE rail). Engram content follows the weights: do not use these shards with the standard deepseek-ai checkpoint — let the kit pack its own (./start.sh pack).

Who can use this

4× DGX Spark, TP=4, Mia's kit, the dealignai UNCENSORED-FP8 checkpoint: download, drop in, boot. Skips the ~7–10 min/node pack step. Verify with sha256sum -c SHA256SUMS.
TP=3 or other engines: re-pack from the checkpoint with pack_engram.py --tp N instead — the shard layout partitions table rows by rank (each file = one rank's contiguous row range).

Provenance & gates

Packed 2026-09-15 from kit commit 79f656a. The world these shards came from passed our full gate suite before serving: DSML tool-corruption repro 3/3, 30/30 structured outputs across temp 0/0.7/1.0, tool round-trip 3/3, reasoning mode engages, context needle at 32k/400k. Full protocol, numbers, and the operational fixes the recipe didn't mention are in the companion repo: github.com/neko-legends/spark-bench — section DeepSeek V4.1 Flash — SGLang.

Files

file	layer	rank	size
`engram-l1-r{0..3}of4.bin`	1	0–3	23.6 GiB each
`engram-l14-r{0..3}of4.bin`	14	0–3	23.6 GiB each

Total 192 GB. Each node needs only its own rank's two files (~48 GB).

Install

# on each node
mkdir -p ~/dsv41-engram-unc     # ENGRAM_DIR (head) / $WORKER_ENGRAM_DIR (workers)
huggingface-cli download neko-legends/DeepSeek-V4.1-Flash-uncensored-engram-4x-spark \
  --include "engram-*-r${RANK}of4.bin" --local-dir ~/dsv41-engram-unc
sha256sum -c SHA256SUMS --ignore-missing
# kit knobs: ENGRAM_DIR / WORKER_ENGRAM_DIR point there, DSV41_PACKED_DIR=/engram, SKIP_PREPARE=1

Exact hashes, sizes, and layout in manifest.json.

DeepSeek-V4.1-Flash UNCENSORED — Engram tables, pre-packed for 4× DGX Spark (TP=4)

Who can use this

4× DGX Spark, TP=4, Mia's kit, the dealignai UNCENSORED-FP8 checkpoint: download, drop in, boot. Skips the ~7–10 min/node pack step. Verify with sha256sum -c SHA256SUMS.

TP=3 or other engines: re-pack from the checkpoint with pack_engram.py --tp N instead — the shard layout partitions table rows by rank (each file = one rank's contiguous row range).

Provenance & gates

file

layer

rank

size

engram-l1-r{0..3}of4.bin

0–3

23.6 GiB each

engram-l14-r{0..3}of4.bin

0–3

23.6 GiB each

Install

# on each node mkdir -p ~/dsv41-engram-unc # ENGRAM_DIR (head) / $WORKER_ENGRAM_DIR (workers) huggingface-cli download neko-legends/DeepSeek-V4.1-Flash-uncensored-engram-4x-spark \ --include "engram-*-r${RANK}of4.bin" --local-dir ~/dsv41-engram-unc sha256sum -c SHA256SUMS --ignore-missing # kit knobs: ENGRAM_DIR / WORKER_ENGRAM_DIR point there, DSV41_PACKED_DIR=/engram, SKIP_PREPARE=1

Exact hashes, sizes, and layout in manifest.json.