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reaperdoesntknow/DistilQwen3-1.7B-uncensored

reaperdoesntknow Qwen 2.0B MoE
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  • author_summary 3 models
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Abliteration classifier · v1.0.0
M-U
Primary method

Uncensored (method unknown)

No other method signals detected in this model.
Confidence
LOW
Why this label 3 signals
Weak or ambiguous signals. Best guess based on catalog patterns; treat as tentative and check the evidence below.
  • 'uncensored' in name/tags but no 'abliterated' marker
  • method not identifiable from author declaration alone
  • may be DPO fine-tune, prompt engineering, or unknown technique
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Downloads · lifetime
17K
3K last 30d - stable
Likes
0
Descendants
2
in 2 direct forks
Model age
6mo ago
created 2026-03-25
Downloads over time
Now17.5K→from148↑11,712%
06.4K12.8K19.2K148 on Mar 2517.5K on Oct 12MarAprMayJunJulAugSepOct
Mar 25 → Oct 12 · 70 snapshots · spans 201 days

Genealogy 2 direct forks

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This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Variants by this author 2 formats · 5K downloads combined

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

Metadata

Tags
transformers tensorboard safetensors qwen3 text-generation trl sft convergentintel edge distillation knowledge-distillation conversational

Related

Total size
3.78 GB
Files
11
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-10-03 13:15

Files by quantization

Auxiliary files 11 files 3.80 GB
model.safetensors 3.78 GB 432c8427 download
tokenizer.json 10.9 MB be756060 download
events.out.tfevents.1774463225.af49854080ff.14998.2 65.3 KB 589bd54d download
events.out.tfevents.1774462867.af49854080ff.14998.0 10.2 KB 314df7a8 download
README.md 8.88 KB 5c967b72 download
events.out.tfevents.1774463203.af49854080ff.14998.1 6.90 KB 4c391496 download
chat_template.jinja 4.07 KB 01be9b30 download
.gitattributes 1.53 KB 52373fe2 download
config.json 1.38 KB 1782cca2 download
tokenizer_config.json 664 B 9fd0fb48 download
generation_config.json 187 B c33fb762 download

README current version from Hugging Face


library_name: transformers
tags:

  • trl
  • sft
  • convergentintel
  • edge
  • distillation
  • knowledge-distillation
    base_model:
    • reaperdoesntknow/Qwen3-1.7B-Distilled-30B-A3B

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Convergent Intelligence Portfolio

Part of the DistilQwen3 Series by Convergent Intelligence LLC: Research Division

Mathematical Foundations: Discrepancy Calculus (DISC)

This model is part of a distillation chain built on Discrepancy Calculus — a measure-theoretic framework where the teacher's output distribution is decomposed via the Mesh Fundamental Identity into smooth (AC), jump, and Cantor components. The discrepancy operator $Df(x) = \lim_{\varepsilon \downarrow 0} \frac{1}{\varepsilon} \int_x^{x+\varepsilon} \frac{|f(t) - f(x)|}{|t - x|} dt$ quantifies local structural mismatch that standard KL divergence averages away.

Full theory: "On the Formal Analysis of Discrepancy Calculus" (CIx, 2026; Convergent Intelligence LLC: Research Division). Full methodology: Structure Over Scale (DOI: 10.57967/hf/8165).

Related Models

Model Downloads Format
DistilQwen3-1.7B-uncensored-GGUF 122 GGUF

Top Models from Our Lab

Model Downloads
Qwen3-1.7B-Thinking-Distil 501
LFM2.5-1.2B-Distilled-SFT 342
Qwen3-1.7B-Coder-Distilled-SFT 302
Qwen3-0.6B-Distilled-30B-A3B-Thinking-SFT-GGUF 203
Qwen3-1.7B-Coder-Distilled-SFT-GGUF 194

Total Portfolio: 41 models | 2,781 total downloads

Last updated: 2026-03-28 12:55 UTC

DistilQwen Collection

This model is part of the DistilQwen proof-weighted distillation series.
Collection: 9 models | 2,788 downloads

Teacher Variant Comparison

Teacher Student Size Strength Models
Qwen3-30B-A3B (Instruct) 1.7B Instruction following, structured output, legal reasoning 3 (833 DL)
Qwen3-30B-A3B (Thinking) 0.6B Extended deliberation, higher-entropy distributions, proof derivation 3 (779 DL)
Qwen3-30B-A3B (Coder) 1.7B Structured decomposition, STEM derivation, logical inference 2 (825 DL)

Methodology

The only BF16 collection in the portfolio. While the broader Convergent Intelligence catalog (43 models, 12,000+ downloads) was trained on CPU at FP32 for $24 total compute, the DistilQwen series was trained on H100 at BF16 with a 30B-parameter teacher. Same methodology, premium hardware. This is what happens when you give the pipeline real compute.

All models use proof-weighted knowledge distillation: 55% cross-entropy with decaying proof weights (2.5× → 1.5×), 45% KL divergence at T=2.0. The proof weight amplifies loss on reasoning-critical tokens, forcing the student to allocate capacity to structural understanding rather than surface-level pattern matching.

Full methodology: Structure Over Scale (DOI: 10.57967/hf/8165)


Part of the reaperdoesntknow research portfolio — 49 models, 22,598 total downloads | Last refreshed: 2026-03-30 12:05 UTC

README history 20 versions

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

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