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Marker689/DeepSeek-V4.1-Flash-1017-EXL3-EAQ-v1-2.9-bpw-Abliterated

Marker689 Deepseek MoE multimodal
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/Marker689%2FDeepSeek-V4.1-Flash-1017-EXL3-EAQ-v1-2.9-bpw-Abliterated"
Response includes
  • classification m1
  • files 49
  • 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 · 30-day
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Model age
today
created 2026-10-25

Genealogy 0 direct forks

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Metadata

License
mit
Languages
en zh
Tags
transformers safetensors deepseek_v41 text-generation deepseek deepseek-v4.1 deepseek-v4.1-flash deepseek-v4.1-flash-1017 exl3 abliterated uncensored tensorfold
Total size
196 GB
Files
49
Quantizations
1
Registered
2026-10-25 02:00
Last updated on HF
2026-10-25 01:49

Files by quantization

Auxiliary files 49 files 196 GB
model-00038-of-00039.safetensors 7.56 GB ******** download
model-00020-of-00039.safetensors 6.56 GB ******** download
model-00019-of-00039.safetensors 6.56 GB ******** download
model-00001-of-00039.safetensors 6.10 GB ******** download
model-00039-of-00039.safetensors 5.42 GB ******** download
model-00002-of-00039.safetensors 4.96 GB ******** download
model-00015-of-00039.safetensors 4.94 GB ******** download
model-00003-of-00039.safetensors 4.87 GB ******** download
model-00009-of-00039.safetensors 4.87 GB ******** download
model-00035-of-00039.safetensors 4.87 GB ******** download
model-00031-of-00039.safetensors 4.87 GB ******** download
model-00036-of-00039.safetensors 4.86 GB ******** download
model-00037-of-00039.safetensors 4.86 GB ******** download
model-00004-of-00039.safetensors 4.86 GB ******** download
model-00005-of-00039.safetensors 4.86 GB ******** download
model-00006-of-00039.safetensors 4.86 GB ******** download
model-00007-of-00039.safetensors 4.86 GB ******** download
model-00008-of-00039.safetensors 4.86 GB ******** download
model-00010-of-00039.safetensors 4.86 GB ******** download
model-00011-of-00039.safetensors 4.86 GB ******** download
model-00029-of-00039.safetensors 4.86 GB ******** download
model-00030-of-00039.safetensors 4.86 GB ******** download
model-00032-of-00039.safetensors 4.86 GB ******** download
model-00033-of-00039.safetensors 4.86 GB ******** download
model-00034-of-00039.safetensors 4.86 GB ******** download
model-00023-of-00039.safetensors 4.86 GB ******** download
model-00027-of-00039.safetensors 4.86 GB ******** download
model-00028-of-00039.safetensors 4.86 GB ******** download
model-00012-of-00039.safetensors 4.86 GB ******** download
model-00013-of-00039.safetensors 4.86 GB ******** download
model-00014-of-00039.safetensors 4.86 GB ******** download
model-00016-of-00039.safetensors 4.86 GB ******** download
model-00017-of-00039.safetensors 4.86 GB ******** download
model-00018-of-00039.safetensors 4.86 GB ******** download
model-00022-of-00039.safetensors 4.86 GB ******** download
model-00024-of-00039.safetensors 4.86 GB ******** download
model-00025-of-00039.safetensors 4.86 GB ******** download
model-00026-of-00039.safetensors 4.86 GB ******** download
model-00021-of-00039.safetensors 3.28 GB ******** download
quantization_config.json 38.2 MB ******** download
model.safetensors.index.json 14.8 MB ******** download
tokenizer.json 6.07 MB 6a15814d download
chat_template.jinja 33.4 KB c5d8fa8a download
config.json 3.48 KB 14e36789 download
README.md 3.29 KB d76d519d download
.gitattributes 1.61 KB 710dc43c download
LICENSE 1.06 KB d62e3bef download
tokenizer_config.json 801 B f3dad388 download
ABLIT_META.json 539 B eaeedc82 download

README current version from Hugging Face


license: mit
language:

  • en
  • zh
    tags:
  • deepseek
  • deepseek-v4.1
  • deepseek-v4.1-flash
  • deepseek-v4.1-flash-1017
  • exl3
  • abliterated
  • uncensored
  • tensorfold
  • dgx-spark
  • gb10
  • moe
  • image-text-to-text
    base_model: Mia-AiLab/DeepSeek-V4.1-Flash-1017-EXL3-EAQ-v1-2.9-bpw
    library_name: transformers
    pipeline_tag: image-text-to-text
    extra_gated_heading: Acknowledge the Responsible Use Agreement to access this repository
    extra_gated_description: Access is granted automatically after you agree to the terms below and submit the form.
    extra_gated_button_content: Agree and request access
    extra_gated_fields:
    Username: text
    Email: text
    Reason for intended use: text
    I am 18 years of age or older: checkbox
    I accept full responsibility for my inputs and any harm from generated content: checkbox
    I will not use this model for sexual exploitation or endangerment of minors: checkbox
    I will not use this model for self-harm, suicide promotion, illegal activity, harassment, doxxing, or fraud: checkbox
    I agree to comply with the upstream DeepSeek base-model license: checkbox
    I agree to the Responsible Use terms in this card: checkbox

DeepSeek-V4.1-Flash-1017 EXL3 2.9 bpw ABliterated

This is a full, self-contained EXL3 checkpoint produced by applying the Keys
abliteration overlay to the Mia-AiLab EAQ-v1 2.9 bpw pack.

Sources and attribution

piece source license
base EXL3 pack Mia-AiLab/DeepSeek-V4.1-Flash-1017-EXL3-EAQ-v1-2.9-bpw MIT
base checkpoint deepseek-ai/DeepSeek-V4.1-Flash-1017 MIT
Keys overlay and sidecar drowzeys/keys-DeepSeek-V4.1-Flash-1017-Abliterated MIT
sidecar used exl3_wo_b_l10_35_mia29.safetensors MIT
engine used for validation TensorFold, bertholomus deepseek-v41-zig family (TensorFold native Zig/CUDA) Apache-2.0 / MIT components

The overlay changes only layers.10-35.attn.wo_b (104 tensors). All experts,
Engram, embed/head, vision, MTP and the remaining tensors are from the stock
pack. MTP dtypes are kept at stock F16 so the native TensorFold drafter reads
mtp.2.confidence_head.proj.weight correctly (n_cast_f32: 0 in ABLIT_META.json).

Format

39 model-*.safetensors EXL3 shards, plus config/tokenizer/index/encoding and
chat_template.jinja. This is the Mia EAQ layout read by the TensorFold
DeepSeek-V4.1 family; it is not a plain Transformers FP16 checkpoint.

Responsible Use

This model has had safety refusals removed, including cybersecurity offense and
defense rails. It is intended for red-teaming, security research, evaluation and
unfiltered assistant tasks. You are responsible for adding appropriate safety
filtering, human review and access controls for your deployment.

Prohibited uses:

  • anything involving the sexual exploitation or endangerment of minors;
  • content promoting self-harm or suicide;
  • material illegal in your jurisdiction, or targeting real individuals for
    harassment, doxxing or fraud;
  • any use prohibited by the upstream DeepSeek license.

You must be 18 or older. The checkpoint is provided as-is, with no warranty.

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