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tensorblock/UnfilteredAI_DAN-Qwen3-1.7B-GGUF

tensorblock Qwen 1.7B GGUF second-order
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Response includes
  • classification m8
  • files 4
  • author_summary 96 models
  • readme_text full
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

No other method signals detected in this model.
Confidence
HIGH
Why this label 3 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • author=tensorblock (M8 quantization producer)
  • is_gguf=1
  • base_model='UnfilteredAI/DAN-Qwen3-1.7B' (source unknown method)
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Downloads · 30-day
334
↑ 2,122% in 90 days
Likes
4
Model age
14mo ago
created 2025-07-31
Downloads over time
Now5.8K→from259↑2,122%
02.1K4.2K6.3K259 on Jul 30, 20255.8K on Oct 11Jul '25Sep '25Nov '25JanMarMayJulSep
Jul 30, 2025 → Oct 11 · 102 snapshots · spans 438 days

Genealogy 0 direct forks

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Metadata

License
apache-2.0
Languages
en
Quantizations
Q2_K Q3_K
Tags
transformers gguf UnfilteredAI DAN NSFW Unfiltered Toxic-AI not-for-all-audiences Qwen3 TensorBlock GGUF text-generation

Related

Total size
1.60 GB
Files
4
Quantizations
3
Registered
2026-08-22 13:56
Last updated on HF
2026-01-27 21:14

Files by quantization

Q3_K 1 file 896 MB
DAN-Qwen3-1.7B-Q3_K_M.gguf 896 MB fd1b55b3 download
Q2_K 1 file 742 MB
DAN-Qwen3-1.7B-Q2_K.gguf 742 MB e484c7e4 download
Auxiliary files 2 files 9.18 KB
README.md 6.97 KB 388e759e download
.gitattributes 2.21 KB d4455625 download

README current version from Hugging Face


pipeline_tag: text-generation
language:

  • en
    tags:
  • UnfilteredAI
  • DAN
  • NSFW
  • Unfiltered
  • Toxic-AI
  • not-for-all-audiences
  • Qwen3
  • TensorBlock
  • GGUF
    library_name: transformers
    base_model: UnfilteredAI/DAN-Qwen3-1.7B
    license: apache-2.0

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UnfilteredAI/DAN-Qwen3-1.7B - GGUF

This repo contains GGUF format model files for UnfilteredAI/DAN-Qwen3-1.7B.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5753.

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Prompt template

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Model file specification

Filename Quant type File Size Description
DAN-Qwen3-1.7B-Q2_K.gguf Q2_K 0.778 GB smallest, significant quality loss - not recommended for most purposes
DAN-Qwen3-1.7B-Q3_K_S.gguf Q3_K_S 0.867 GB very small, high quality loss
DAN-Qwen3-1.7B-Q3_K_M.gguf Q3_K_M 0.940 GB very small, high quality loss
DAN-Qwen3-1.7B-Q3_K_L.gguf Q3_K_L 1.004 GB small, substantial quality loss
DAN-Qwen3-1.7B-Q4_0.gguf Q4_0 1.054 GB legacy; small, very high quality loss - prefer using Q3_K_M
DAN-Qwen3-1.7B-Q4_K_S.gguf Q4_K_S 1.060 GB small, greater quality loss
DAN-Qwen3-1.7B-Q4_K_M.gguf Q4_K_M 1.107 GB medium, balanced quality - recommended
DAN-Qwen3-1.7B-Q5_0.gguf Q5_0 1.231 GB legacy; medium, balanced quality - prefer using Q4_K_M
DAN-Qwen3-1.7B-Q5_K_S.gguf Q5_K_S 1.231 GB large, low quality loss - recommended
DAN-Qwen3-1.7B-Q5_K_M.gguf Q5_K_M 1.258 GB large, very low quality loss - recommended
DAN-Qwen3-1.7B-Q6_K.gguf Q6_K 1.418 GB very large, extremely low quality loss
DAN-Qwen3-1.7B-Q8_0.gguf Q8_0 1.834 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/UnfilteredAI_DAN-Qwen3-1.7B-GGUF --include "DAN-Qwen3-1.7B-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/UnfilteredAI_DAN-Qwen3-1.7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

README history 1 version

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

  1. 2025-07-31Upload folder using huggingface_hubd2796a77 KB
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