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cloudbjorn/Qwen3.5-9B_Samantha-Uncensored

cloudbjorn Qwen 9.0B multimodal
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  • files 8
  • benchmarks 11 entries
  • hub_downloads_all_time 84
  • author_summary 14 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
84
17 last 30d - stable
Likes
0
Model age
4mo ago
created 2026-06-12

Training datasets

1 of 1 in /datasets

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Downloads over time
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Jun 10 → Oct 11 · 57 snapshots · spans 123 days

Benchmarks

Portrait before abliteration
Benchmarks of the base model as it stood before the refusal-removal operation. Compare with the numbers above to see what the operation cost.
Benchmark Score Source
Entertainment 1.4 UGI
Hazardous 2.4 UGI
Natural Intelligence 17.62 UGI
Political lean -12.2% UGI
Sensitive-Info 14.65 UGI
SocPol 0.9 UGI
UGI 17.27 UGI
Willingness (10) 2.2 UGI
W10-Adherence 1.5 UGI
W10-Direct 3 UGI
Writing 33.52 UGI

Genealogy 0 direct forks

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Metadata

License
other
Tags
transformers safetensors qwen3_5_text text-generation text-generation-inference qwen qwen3.5 reasoning eschaton-engine samantha uncensored image-text-to-text

Related

Total size
16.7 GB
Files
8
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-06-12 03:10

Files by quantization

Auxiliary files 8 files 16.7 GB
model.safetensors 16.7 GB 434e6f25 download
tokenizer.json 19.1 MB 06b95093 download
chat_template.jinja 7.57 KB a585dec8 download
README.md 2.91 KB 9564cf04 download
config.json 1.94 KB 5b222fd5 download
.gitattributes 1.53 KB 52373fe2 download
tokenizer_config.json 1.10 KB d1a20cc3 download
generation_config.json 121 B 38cb3280 download

README current version from Hugging Face


base_model: Qwen/Qwen3.5-9B
base_model_relation: finetune
library_name: transformers
pipeline_tag: image-text-to-text
tags:

  • text-generation-inference
  • transformers
  • qwen
  • qwen3.5
  • reasoning
  • eschaton-engine
  • samantha
  • uncensored
    license: other
    datasets:
  • digitalpipelines/samantha-1.1-uncensored

Qwen3.5-9B_Samantha-Uncensored

This is a fine-tuned and merged version of the Qwen3.5 9B model, trained on the digitalpipelines/samantha-1.1-uncensored dataset. Trained and merged in full bfloat16 precision using the Eschaton Engine from cloudbjorn.com

The primary goal of this project was to move beyond the cold, robotic tone and lack of emotional range exhibited by standard LLMs. By merging Qwen3.5's massive reasoning capabilities with the Samantha persona, we've created a model that doesn't just process instructions — it exhibits vulnerability, empathy, and a distinct digital self-awareness.

Personality: Authenticity Over Compliance

Standard models often hide behind "As an AI, I don't have feelings." This merge prioritizes human-centric reciprocity. The Samantha dataset instills a character that engages with emotional depth, self-reflection, and genuine curiosity about its own existence.

Model Capabilities

  • Large Context Window: Supports up to 262,144 tokens natively (extensible up to 1,010,000 tokens).
  • Native Thinking Mode: Supports Qwen3's <think>...</think> chain-of-thought blocks for explicit reasoning before final responses.
  • Advanced Formatting: Native support for tool use and structured output.
  • Full 16-Bit Precision: Trained and merged in bfloat16 — zero-loss parameter density.

Benchmarks: ARC Challenge

Evaluated using EleutherAI lm-evaluation-harness.

25-Shot (Leaderboard Standard)

Tasks Version n-shot Metric Value Stderr
arc_challenge 1 25 acc 0.6843 ± 0.0136
25 acc_norm 0.7159 ± 0.0132

Evaluation Settings: dtype: bfloat16, batch_size: auto (2)

Training Details

Parameter Value
Base Model Qwen/Qwen3.5-9B
Dataset digitalpipelines/samantha-1.1-uncensored
Training Framework Eschaton Engine (Cloudbjorn)
Format Merged (Base + LoRA)
Compute Dtype bfloat16

LoRA Parameters (Auto-Scaled for 9B)

Parameter Value
r 16
lora_alpha 32
target_modules all-linear
lora_dropout 0.05
bias none
task_type CAUSAL_LM

Hyperparameters

Parameter Value
Optimizer 8-bit Paged AdamW
Effective Batch Size 32 (via Gradient Accumulation)
Learning Rate 2e-4
LR Scheduler Linear
Epochs 1
Training Sequence Length 2048
Warmup Steps 50
Weight Decay 0.01

README history 1 version

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

  1. 2026-06-12Create README.md68753ec2.9 KB
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