license: mit base_model: s-zaizen/DeepSeek-V4.1-Flash-Abliterated tags:
- deepseek
- deepseek_v41
- abliterated
- uncensored
- gguf
- iq2_xxs
- q2_k
- moe
DeepSeek-V4.1-Flash-Abliterated-Q2-GGUF
DwarfStar Q2 GGUF of the community-abliterated DeepSeek V4.1 Flash checkpoint
(s-zaizen/DeepSeek-V4.1-Flash-Abliterated, itself abliterated from
deepseek-ai/DeepSeek-V4.1-Flash with Heretic;
refusal keyword rate reported there as 97/100 → 24/100).
Two files: ...-imatrix.gguf (recommended) and the original
DeepSeek-V4.1-Flash-Abliterated-Q2.gguf bootstrap build (kept for
reference; the imatrix build supersedes it).
Recipe
Converted with deepseek41_quantize.py (DwarfStar ds4 repo) using the
project's C quantizers, --quant q2, imatrix-calibrated routed experts
(16-prompt / 26K-token calibration collected on the abliterated Q2):
- Routed MoE experts:
IQ2_XXSgate/up,Q2_Kdown (imatrix-guided on the stock recipe; bootstrap here — an imatrix-calibrated v2 may follow) - Attention, shared experts, projections, output:
Q8_0/ F16 - Engram FP8 rows packed losslessly at end of file (read from disk as needed, never resident)
deepseek41_validate_gguf.py layout audit: PASS (1046 tensors).
Quality vs stock Q2
Target-token NLL on 100 tracked official V4.1 Flash continuations
(deepseek-v4.1-flash-20260910-general, ctx 4096, SSD streaming),
same harness for both files:
| file | mean NLL | median NLL | first-token match | top-1 agreement |
|---|---|---|---|---|
stock DeepSeek-V4.1-Flash-Q2 | 0.346 | 0.313 | 78/100 | 0.901 |
| bootstrap build | 0.395 | 0.395 | 71/100 | 0.888 |
| imatrix build (this file) | 0.359 | 0.340 | 80/100 | 0.904 |
Essentially at parity with stock: the remaining ~0.01 NLL is plausibly the ablation itself. First-token match and top-1 agreement beat stock within noise.
Use
Built for DwarfStar ds4 (docs/MODELS.md
"DeepSeek V4.1 Flash"). It is not a general GGUF: the tensor layout,
quantization mix, and Engram packing are ds4-specific.
./download_model.sh ds41f-q2 # stock weights instead (341 GiB)
./ds4 -m DeepSeek-V4.1-Flash-Abliterated-Q2.gguf --ssd-streaming --ctx 32768
On one 128 GB Mac, use --ssd-streaming (152 GiB main weights; Engram
tables stay on disk). Needs a fast local SSD.
License
Base weights © DeepSeek, MIT (retained via the source checkpoint). Conversion tooling per the ds4 repo license.