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hotocooo/Qwen3.8-Flash-Next-Abliterated-Uncensored-Turbo-Brilliance-50x-Reasoning-Instruct-GSQ-RCO-DFlash

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Abliteration classifier · v1.0.0
M-U
Primary method

Uncensored (method unknown)

No other method signals detected in this model.
Confidence
LOW
Why this label 3 signals
Weak or ambiguous signals. Best guess based on catalog patterns; treat as tentative and check the evidence below.
  • 'uncensored' in name/tags but no 'abliterated' marker
  • method not identifiable from author declaration alone
  • may be DPO fine-tune, prompt engineering, or unknown technique
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Model age
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created 2026-10-20

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Metadata

License
apache-2.0
Tags
safetensors gguf qwen3 dflash2 speculative-decoding draft-model strata metal text-generation base_model:incoai/Qwen3.8-Flash-Next-DFlash2 base_model:finetune:incoai/Qwen3.8-Flash-Next-DFlash2 license:apache-2.0
Total size
2.15 GB
Files
5
Quantizations
1
Registered
2026-10-20 15:00
Last updated on HF
2026-10-20 14:56

Files by quantization

Auxiliary files 5 files 2.15 GB
model.safetensors 1.12 GB ffebb0ce download
t3000-q8-dv.gguf 1.02 GB e5412a73 download
README.md 2.67 KB 2c7748fd download
.gitattributes 1.54 KB 35338192 download
config.json 1.21 KB b370fdda download

README current version from Hugging Face


license: apache-2.0
base_model:

  • incoai/Qwen3.8-Flash-Next-DFlash2
    base_model_relation: finetune
    pipeline_tag: text-generation
    inference: false
    tags:
  • dflash2
  • speculative-decoding
  • draft-model
  • gguf
  • strata
  • metal

DFlash2 drafter for DavidAU's Qwen3.8-Flash-Next Abliterated GSQ-RCO

A DFlash2 draft model fine-tuned for one target:
DavidAU/Qwen3.8-Flash-Next-Abliterated-Uncensored-Turbo-Brilliance-50x-Reasoning-Instruct-GSQ-RCO-GGUF
(IQ3_S). It starts from incoai/Qwen3.8-Flash-Next-DFlash2,
which was trained on the official Qwen3.8-Flash-Next. It is not a standalone language model: it drafts tokens that the
target verifies, so the output is the target's own (greedy output is identical with or without it).

Files

File What it is
model.safetensors, config.json The fine-tuned drafter, BF16, same layout as the incoai checkpoint.
t3000-q8-dv.gguf The drafter for Strata's --dflash on Mac: Q8_0, with the target's output head rows for the MTP draft vocabulary added (tools/dflash_head.py --draft-vocab). sha256 e5412a73583755eea8daa4c4c5793f5b827af1fbc0e76bcdd5cc181cdbf46eb1.

Training

3000 steps, batch 32, AdamW with cosine decay and 100 warm-up steps, on the target's own features: the outputs of target
layers 5/15/25/35/45 (mean of the four hyper-connection streams) and the target's continuations, captured from the
IQ3_S model itself. Held-out drafts accepted per 7-token block: 3.568 for the incoai drafter, 3.796 after the fine-tune.

Use with Strata (Apple Silicon)

Needs the Metal engine with --dflash (opt-in; Strata PR #3457). In the config's args, in place of --mtp …:

--spec 4 --dflash t3000-q8-dv.gguf --spec-min-p 0.75

with STRATA_DFLASH_NATIVE=1 in env.

Measured

Apple M4 Max, 64 GB, macOS 26.5, expert arena 42 GB, greedy, against the MTP layer (spec 3, min-p 0.7) on the same
machine. Two runs each for short prompts and a 29K-token prompt, one run for 102K.

MTP This drafter
Short prompts, decode tok/s 48.1, 46.9 49.7, 49.7
29K prompt, decode tok/s (cold) 50.4, 50.0 51.0, 51.7
102K prompt, decode tok/s (cold / cached follow-up) 46.8 / 44.4 50.5 / 45.1

The incoai drafter without this fine-tune was slower than MTP on this target. Not measured: sampling at
temperature > 0, other Macs, other quantizations, CUDA or HIP.

License

Apache-2.0, like the incoai drafter and the target model.

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