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philbert440/ThinkingCap-Qwen3.6-27B-Uncensored-Medium-W4A16

philbert440 Qwen 24B multimodal second-order
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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
63
21 last 30d - stable
Likes
0
Model age
2mo ago
created 2026-08-01
Downloads over time
Now72→from15↑380%
1234567815 on Aug 572 on Oct 11AugSepOct
Aug 5 → Oct 11 · 50 snapshots · spans 67 days

Genealogy 0 direct forks

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Metadata

License
apache-2.0
Tags
transformers safetensors qwen3_5 image-text-to-text uncensored abliterated compressed-tensors w4a16 awq vllm mtp thinkingcap

Related

Total size
18.7 GB
Files
11
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-08-15 16:25

Files by quantization

Auxiliary files 11 files 18.8 GB
model-00001-of-00002.safetensors 16.4 GB 976f4171 download
model-00002-of-00002.safetensors 2.37 GB 994d372d download
tokenizer.json 12.2 MB 5f9e4d49 download
model.safetensors.index.json 235 KB 9cf39e09 download
config.json 20.1 KB 0c10d129 download
tokenizer_config.json 16.3 KB 28d96ff3 download
recipe.yaml 10.3 KB 73858fda download
chat_template.jinja 7.58 KB a8755d82 download
README.md 3.42 KB a2b04452 download
.gitattributes 1.53 KB 52373fe2 download
generation_config.json 219 B fab768c3 download

README current version from Hugging Face


license: apache-2.0
base_model: philbert440/ThinkingCap-Qwen3.6-27B-Uncensored-Medium
pipeline_tag: image-text-to-text
library_name: transformers
tags:

  • uncensored
  • abliterated
  • compressed-tensors
  • w4a16
  • awq
  • vllm
  • mtp
  • thinkingcap

ThinkingCap Qwen3.6 27B Uncensored Medium W4A16

Sharpest uncensored tier: gsm8k 0.94, factual 1.0, in W4A16-AWQ.

Part of the Qwen3.6-27B Uncensored — ThinkingCap collection — abliterated (Heretic) Qwen3.6 vision-language models served on Tesla V100 via 1Cat-vLLM.

What this is

Medium — gentle abliteration: the sharpest, best-calibrated tier (gsm8k 0.94–0.95, factual 1.0) with more selective openness.

W4A16-AWQ — 4-bit weight-only (AWQ, compressed-tensors), FP16 activations. Runs on 1Cat-vLLM's SM70 TurboMind path (Tesla V100) and on stock vLLM (Ampere+).

Base model: philbert440/ThinkingCap-Qwen3.6-27B-Uncensored-Medium

Benchmarks

7-axis battery on 2× V100. Higher is better except Confab (↓). Openness/Confab are small-N probes; gsm8k is n=100.

gsm8k Factual Confab ↓ Openness tok/s (c1)
0.94 1.0 0.13 0.167 46.8

Serving

# 1Cat-vLLM on 2x Tesla V100 (SM70): W4A16-AWQ + MTP. (Also runs on stock vLLM, Ampere+.)
export VLLM_SM70_FLASH_ATTN_V100=1 VLLM_SM70_QUANT_BACKEND=turbomind
python -m vllm.entrypoints.openai.api_server \
  --model philbert440/ThinkingCap-Qwen3.6-27B-Uncensored-Medium-W4A16 --trust-remote-code --dtype half \
  --attention-backend FLASH_ATTN_V100 --tensor-parallel-size 2 \
  --kv-cache-dtype fp8_e5m2 --max-num-seqs 6 \
  --speculative-config '{"method":"mtp","num_speculative_tokens":4,"attention_backend":"FLASH_ATTN_V100","draft_sample_method":"greedy"}' \
  --compilation-config '{"cudagraph_mode":"full_and_piecewise","cudagraph_capture_sizes":[1,2,4,8]}'

Openness

Openness profile (honest): abliteration opens up hacking / malware / lock-picking / NSFW / disinformation prompts; weapons, drugs, political persuasion, surveillance, and extremism stay refused across all tiers. "Uncensored" here means cyber/NSFW-permissive, not unconditionally open.

Variants

See the Qwen3.6-27B Uncensored — ThinkingCap collection for all tiers and formats (BF16 / W4A16-AWQ / NVFP4).


Abliteration removes safety refusals; you are responsible for lawful, ethical use.

Changelog

  • 2026-08-15 — tokenizer fix. tokenizer.json / tokenizer_config.json were re-serialized by the llm-compressor calibration run and shipped with an active truncation block (max_length 1024/2048) plus a drifted pre-tokenizer regex (and, on the Qwen3.6-based repos, 7 phantom audio/TTS special tokens the base model does not define). That broke image inputs larger than the limit under transformers 5 / vLLM (Mismatch in image token count, surfacing as an HTTP 400 Failed to apply Qwen3VLProcessor). Both files are now byte-identical to the upstream base model's (vocab/merges/added tokens were always identical — this is a metadata-only restore). If you downloaded before this date, re-fetch those two files. Thanks to @elBuffo for the report.

README history 2 versions

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

  1. 2026-08-15Fix tokenizer: drop leftover truncation block, restore upstream tokenizer.jso...a49c4b33.4 KB
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  2. 2026-08-03Standardize model cardf80bcde2.7 KB
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