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tomvaillant/qwen3-4b-abliterated-v2-journalist

tomvaillant Qwen 4B second-order
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  • classification m1
  • files 7
  • author_summary 5 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)
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Model age
5mo ago
created 2026-04-17
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Variants by this author 2 formats · 18 downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

License
apache-2.0
Languages
en
Tags
transformers safetensors text-generation-inference unsloth qwen3 trl investigative-journalism osint lora adapter conversational en

Related

Total size
126 MB
Files
7
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-06-17 12:00

Files by quantization

Auxiliary files 7 files 137 MB
adapter_model.safetensors 126 MB 9cc482a9 download
tokenizer.json 10.9 MB 476870a1 download
chat_template.jinja 4.02 KB 699ff8df download
README.md 2.05 KB 12d380ca download
.gitattributes 1.53 KB 52373fe2 download
adapter_config.json 1.23 KB dd258ad5 download
tokenizer_config.json 374 B c35dc4cf download

README current version from Hugging Face


license: apache-2.0
base_model: huihui-ai/Huihui-Qwen3-4B-abliterated-v2
language:

  • en
    tags:
  • transformers
  • text-generation-inference
  • unsloth
  • qwen3
  • trl
  • investigative-journalism
  • osint
  • lora
  • adapter
  • conversational

qwen3-4b-abliterated-v2-journalist

LoRA adapter for investigative journalism and OSINT workflows, fine-tuned from huihui-ai/Huihui-Qwen3-4B-abliterated-v2.

This is the adapter checkpoint. For browser/WebGPU inference, use the ONNX export:

Training

  • Method: QLoRA with Unsloth + TRL SFT
  • Base model: huihui-ai/Huihui-Qwen3-4B-abliterated-v2
  • Dataset: tomvaillant/investigative-journalism-training
  • Task: compact local/browser assistant for OSINT tool choice, verification, investigation planning, and source handling

Sources And Attribution

Training data: tomvaillant/investigative-journalism-training — 687 instruction/response pairs synthesized by Claude Opus 4.6 (Anthropic) from the Buried Signals OSINT and investigative-journalism corpus: OSINT Navigator tool data, Indicator Media briefings, Buried Signals investigative skills, GIJN, Bellingcat, Verification Handbook 3, SPJ Code of Ethics, RCFP, and public manuals from UNESCO, Al Jazeera Media Institute, CiFAR, CIPE, and EJF/TEMPO Institute.

See the dataset card for the full source list, licenses, and per-partner attribution.

Intended Use

Designed for journalist-facing local inference and browser deployment. It can suggest workflows, tools, search strategies, and verification steps. Generated URLs, claims, and legal guidance must be checked against primary sources.

This was trained with Unsloth.

README history 3 versions

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

  1. 2026-06-17Point attribution to dataset card (single source of truth)dd8f75c2.1 KB
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  2. 2026-04-30Add model card493ef651.9 KB
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  3. 2026-04-17Upload README.md with huggingface_huba305a41573 B
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