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nesaorg/PonyRealism-Uncensored

nesaorg 2.6B image-gen
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Response includes
  • classification m-uncensored
  • files 3
  • hub_downloads_all_time 888
  • author_summary 3 models
  • readme_text full
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What "m-uncensored" means · taxonomy
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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
How we label → About M-U →
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
888
79 last 30d - cooling
Likes
3
Model age
18mo ago
created 2025-04-16
Downloads over time
Now909→from0↑0%
033366710000 on Feb 12, 2025909 on Oct 11Feb '25May '25Aug '25Nov '25FebMayAug
Feb 12, 2025 → Oct 11 · 126 snapshots · spans 606 days

Metadata

Tags
diffusers safetensors arxiv:1910.09700 endpoints_compatible diffusers:StableDiffusionXLPipeline region:us

Related

Other by nesaorg
LazyMix-Uncensored 2K Flux-1.0-uncensored 0
Total size
0 B
Files
3
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-04-16 22:20
Source huggingface.co/nesaorg/PonyRealism-Uncensored ↗

Files by quantization

Auxiliary files 3 files 7.18 KB
README.md 5.04 KB 62926272 download
.gitattributes 1.48 KB a6344aac download
model_index.json 676 B 9e1036df download

README current version from Hugging Face

library_name: diffusers

Model Card for Model ID

Model Details

Model Description

This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.

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Model Sources [optional]

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Uses

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

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Training Procedure

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Evaluation

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Results

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Summary

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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README history 1 version

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

  1. 2025-04-16Upload StableDiffusionXLPipeline473ac015 KB
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