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Wastaken90/DeepSeek-V4-Abliterated-Demo

Wastaken90 Deepseek
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Response includes
  • classification m1
  • files 5
  • author_summary 1 models
  • readme_text full
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GET/models?family=deepseek&method=m1
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What "m1" means · taxonomy
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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)
How we label → About M1 →
Refusal direction extracted via
Extraction technique

Difference-of-means

FromArditi et al. (2024) ↗
Confidence
MEDIUM
Why we say so
primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)
What is a refusal direction? → Read the paper ↗
Downloads · 30-day
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Model age
2mo ago
created 2026-08-04
Downloads over time
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00110 on Aug 50 on Oct 11AugSepOct
Aug 5 → Oct 11 · 50 snapshots · spans 67 days

Metadata

Tags
region:us
Total size
0 B
Files
5
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-08-04 00:31
Source huggingface.co/Wastaken90/DeepSeek-V4-Abliterated-Demo ↗

Files by quantization

Auxiliary files 5 files 54.9 KB
index.html 31.4 KB d7f8a94f download
app.py 10.5 KB d1db4d9f download
requirements.txt 10.5 KB d1db4d9f download
.gitattributes 1.48 KB a6344aac download
README.md 922 B 77a86ccc download

README current version from Hugging Face

title: DeepSeek-V4-Flash-DSpark-Abliterated
emoji: 🔥
colorFrom: purple
colorTo: blue
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false

DeepSeek-V4-Flash-DSpark-Abliterated Demo

🔥 Abliterated (uncensored) DeepSeek-V4-Flash with 1M context window.

Model Specifications

Metric Value
Parameters 284B MoE / ~13B active
Context 1,048,576 tokens
C1 Decode ~57 tok/s
Refusal Bypass ~100%

How to Use

  1. Enter your vLLM API endpoint in the settings
  2. Adjust temperature and max tokens as needed
  3. Start chatting!

Hardware Requirements

This model requires 2× NVIDIA DGX Spark (GB10) servers with vLLM and kv_cache_dtype=nvfp4_ds_mla.

Disclaimer

⚠️ This model has safety refusals removed. You are responsible for adding appropriate safety filtering, human review, and access controls for your deployment.

README history 2 versions

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

  1. 2026-08-04Upload README.md with huggingface_hubb447ad8922 B
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  2. 2026-08-04Upload folder using huggingface_hubca3c9c9776 B
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