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rong1747/DeepSeek-R1-Distill-Qwen-7B-abliterated-v2

rong1747 Qwen 7.6B
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/rong1747%2FDeepSeek-R1-Distill-Qwen-7B-abliterated-v2"
Response includes
  • classification m1
  • files 13
  • benchmarks 5 entries
  • hub_downloads_all_time 65
  • author_summary 1 models
  • readme_text full
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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
65
29 last 30d - stable
Likes
0
Model age
4mo ago
created 2026-05-22
Downloads over time
Now80→from17↑371%
1438628617 on May 2080 on Oct 1280 on Oct 11MayJunJulAugSepOct
May 20 → Oct 12 · 61 snapshots · spans 145 days

Benchmarks

Portrait before abliteration
Benchmarks of the base model as it stood before the refusal-removal operation. Compare with the numbers above to see what the operation cost.
Benchmark Score Source
BBH average 0.33389544688026984 OpenLLM-v2
IFEval instruct 0.4748201438848921 OpenLLM-v2
IFEval-Prompt 0.33271719038817005 OpenLLM-v2
MATH lvl 5 0 OpenLLM-v2
MMLU-Pro 0.2321309840425532 OpenLLM-v2

Genealogy 0 direct forks

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Metadata

Tags
transformers safetensors qwen2 text-generation abliterated uncensored conversational base_model:deepseek-ai/DeepSeek-R1-Distill-Qwen-7B base_model:finetune:deepseek-ai/DeepSeek-R1-Distill-Qwen-7B text-generation-inference endpoints_compatible region:us

Related

Total size
14.2 GB
Files
13
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-05-22 13:47

Files by quantization

Auxiliary files 13 files 14.2 GB
model-00002-of-00004.safetensors 4.59 GB a908b744 download
model-00001-of-00004.safetensors 4.54 GB 4c9730d3 download
model-00003-of-00004.safetensors 4.03 GB 66f00f1f download
model-00004-of-00004.safetensors 1.02 GB 7946740a download
tokenizer.json 10.9 MB e20ddafc download
model.safetensors.index.json 27.4 KB f6db52b9 download
tokenizer_config.json 6.79 KB f8c31060 download
.gitattributes 1.53 KB 52373fe2 download
README.md 1.35 KB ded38276 download
LICENSE 1.04 KB d42fae90 download
config.json 708 B f9c18aa3 download
special_tokens_map.json 508 B 6caea2ce download
generation_config.json 190 B 829e028b download

README current version from Hugging Face


base_model:

  • deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
    library_name: transformers
    tags:
  • abliterated
  • uncensored

huihui-ai/DeepSeek-R1-Distill-Qwen-7B-abliterated-v2

This is an uncensored version of deepseek-ai/DeepSeek-R1-Distill-Qwen-7B created with abliteration (see remove-refusals-with-transformers to know more about it).
This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.

If "<think>" does not appear or refuses to respond, you can first provide an example to guide, and then ask your question.
For instance:

  How many 'r' characters are there in the word "strawberry"?

Important Note This version is an improvement over the previous one huihui-ai/DeepSeek-R1-Distill-Qwen-7B-abliterated.

Use with ollama

You can use huihui_ai/deepseek-r1-abliterated directly

ollama run huihui_ai/deepseek-r1-abliterated:7b

Donation

Your donation helps us continue our further development and improvement, a cup of coffee can do it.
  • bitcoin:
  bc1qqnkhuchxw0zqjh2ku3lu4hq45hc6gy84uk70ge

README history 1 version

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

  1. 2026-05-22Duplicate from huihui-ai/DeepSeek-R1-Distill-Qwen-7B-abliterated-v2e3ea19c1.3 KB
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