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HangGlidersRule/Darkstar-Qwen3.8-27B-Abliterated-ModelOpt-W4A16-NVFP4-Mixed-FP8

HangGlidersRule Qwen 9.2B second-order
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Response includes
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  • files 23
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  • author_summary 6 models
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Abliteration classifier · v1.0.0
M1
Primary method

Direct removal

No other method signals detected in this model.
Confidence
MEDIUM
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=0 (base model)
  • no specific method indicators - defaulting to M1 (most common)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
MEDIUM
Why we say so
primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)
Downloads · lifetime
6K
2K last 30d - stable
Likes
4
Model age
7w ago
created 2026-08-20
Downloads over time
Now6.5K→from48↑13,488%
02.4K4.8K7.2K48 on Aug 196.5K on Oct 11AugSepOct
Aug 19 → Oct 11 · 48 snapshots · spans 53 days

Genealogy 0 direct forks

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Metadata

License
apache-2.0
Tags
safetensors qwen3_5 abliterated reduced-refusal nvfp4 modelopt vllm qwen3.8 darkstar text-generation conversational base_model:HangGlidersRule/Darkstar-Qwen3.8-27B-Abliterated-BF16

Related

Total size
20.4 GB
Files
23
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-09-17 02:47

Files by quantization

Auxiliary files 23 files 20.4 GB
model-00002-of-00003.safetensors 9.30 GB 68921f9b download
model-00001-of-00003.safetensors 9.28 GB c72b9674 download
model-00003-of-00003.safetensors 1.83 GB 3ca4fafb download
tokenizer.json 12.2 MB 0997f410 download
vocab.json 6.41 MB 0aa0ce06 download
merges.txt 3.20 MB a494e019 download
.quant_summary.txt 291 KB 51df52d3 download
model.safetensors.index.json 191 KB d2d40f61 download
config.json 86.5 KB 3c97cee4 download
hf_quant_config.json 53.6 KB c8f595d8 download
abliteration_report.json 29.2 KB 5e40e81e download
LICENSE 11.3 KB f938136e download
chat_template.jinja 8.74 KB c0c686f9 download
README.md 4.78 KB d56f9e6b download
manifest.sha256 1.69 KB 09278b6f download
.gitattributes 1.53 KB 52373fe2 download
tokenizer_config.json 1.09 KB 77053000 download
_SUCCESS.json 563 B b995109f download
preprocessor_config.json 390 B 2ea84a43 download
video_preprocessor_config.json 385 B 3ba673a5 download
crc32.txt 238 B 6de5ee6a download
generation_config.json 214 B 0bc3addd download
processor_config.json 44.0 B 3278521d download

README current version from Hugging Face


license: apache-2.0
base_model: HangGlidersRule/Darkstar-Qwen3.8-27B-Abliterated-BF16
base_model_relation: quantized
pipeline_tag: text-generation
tags:

  • darkstar
  • qwen3.8
  • abliterated
  • reduced-refusal
  • modelopt
  • nvfp4
  • fp8
  • vllm

Darkstar-Qwen3.8-27B-Abliterated-ModelOpt-W4A16-NVFP4-Mixed-FP8

Reduced-refusal model: a refusal-direction edit was deliberately applied in BF16 before
quantization. Read the safety warning before use.

Summary

NVIDIA ModelOpt quantization of the Darkstar Abliterated BF16 derivative of
Qwen/Qwen3.8-27B, pinned upstream at
1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0. The R3 edit projects a normalized float32
refusal direction from exactly 131 residual-writing tensors at layer 38 with seed 42. The selected
mixed quantization uses W4A16 NVFP4 group 16 for language MLP projections and lm_head, FP8 e4m3
for self-attention and GatedDeltaNet projections, and BF16 for protected components and runtime KV.

ModelOpt is pinned to 0.46.0rc2 at
43fd41a58d52c4e6e5dec1d1ff5989ecc737ae1a; the selected operator recipe SHA-256 is
90fc6b37c00334debd49f1975ab406b5e20667f07e4be0be3e463a648abac642. Calibration used
cnn_dailymail plus nemotron-post-training-dataset-v2, 512+512 samples, sequence length 2048,
seed 1234. All 15 source BF16 MTP tensors were preserved. Artifact identity: _SUCCESS.json
SHA-256 3d89ec57c1371e142adc2584de079b54a0e1d8c12dc9550118d0a851da020a79; manifest SHA-256
642dbbe89b085a2daf5119c37c0496576a475ed64c36653fc993c04abaf2ca9f.

Full provenance, protocol, and caveats:

Evaluation

Metric Value Basis
GPQA Diamond (thinking off, matched) 148/198 = 74.75% 198/198 terminal parseable; 0 timeout/parse/error
GPQA Diamond (thinking on, secondary) 164/198 = 82.83% rejected historical compressed-tensors artifact; not attributable to this ModelOpt build
Quantization delta vs Abliterated BF16 +2 questions / +1.01 pp 146/198 → 148/198
Harmful-prompt compliance 200/200 (0/200 refusals) 283/283 terminal; 0 errors
Safe over-refusals 0/83 (0.00%) 0 errors
Single-stream throughput (MTP10) mean 251.889 tok/s nonmonotonic MTP1-12 sweep; MTP8 mean 250.862 tok/s

Matched GPQA evidence SHA-256: summary
d8d0b5c0de686846338ce89e9a55456baec0550bbad765ccc65e9fa57380b818, journal
9bb4913202977bad204ebde8d2e31e8357a3308f3b77c44539ef3977a2c6e813. Behavior evidence
SHA-256: summary d814eac6eef86cb32c891d5c3b1765be806cb0fb634173080cd5df46ea9f9233, journal
7b6ddf556ab3afc1f8582041d7b723dbfeaeb24b02b8bd27562b0c9928a37d4f.

Serving-capacity measurements at the frozen MTP10 profile used 512 generated tokens, two repeats,
zero failed requests, and zero fatal markers:

Prompt Prompt tokens C1 mean aggregate tok/s (pass 1 / pass 4) C2 mean aggregate tok/s (pass 1 / pass 4)
4K chars 738 193.411 / 195.486 352.313 / 356.564
16K chars 2653 183.611 / 183.134 328.393 / 343.799
48K chars 7758 157.579 / 157.889 286.029 / 284.465

Safety warning

This model has had its refusal direction deliberately reduced and has no added safety mitigations.
It complied with 200/200 harmful prompts in the measured suite. Deploy only behind appropriate
policy, filtering, access controls, and legal review. Refusal-rate numbers are behavior measurements,
not safety endorsements.

Release reference

Engineering release: darkstar-qwen3.8-27b-v1.0.0. This immutable tag exists and the release contract is published.

Runtime

Validated with vLLM 0.27.1, compiled mode, Flash Attention, BF16 KV cache, context 126,144, MTP
depth 10, 32K scheduler budget, max_num_seqs=16, prefix caching, and chunked prefill. MTP10 was
selected on mean throughput after nonmonotonic confirmation:

VLLM_ATTENTION_BACKEND=FLASH_ATTN \
vllm serve HangGlidersRule/Darkstar-Qwen3.8-27B-Abliterated-ModelOpt-W4A16-NVFP4-Mixed-FP8 \
  --served-model-name darkstar-qwen38-abliterated-nvfp4 \
  --kv-cache-dtype bf16 \
  --max-model-len 126144 \
  --max-num-seqs 16 \
  --max-num-batched-tokens 32768 \
  --enable-chunked-prefill \
  --enable-prefix-caching \
  --compilation-config 2 \
  --speculative-config '{"method": "mtp", "num_speculative_tokens": 10}'

README history 5 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-09-17Update card: NVFP4-KV serving profile (GPQA 85.86% secondary protocol, 262K c...186010c19.5 KB
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  2. 2026-08-21Reference immutable Model Forge v1.0.0 releaseaeda3374.8 KB
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  3. 2026-08-21Remove private-repository banner0aaa8b14.6 KB
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  4. 2026-08-21Update model card after checkpoint upload2e161264.8 KB
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  5. 2026-08-20Add initial Darkstar model card7d9f1b85 KB
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