← back to catalog · registered 2026-08-22 13:56

Guilherme34/GPT-OSS-UNCENSORED_MAKING-20B

Guilherme34 Gpt-oss 20B
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/Guilherme34%2FGPT-OSS-UNCENSORED_MAKING-20B"
Response includes
  • classification m-uncensored
  • files 14
  • hub_downloads_all_time 23
  • author_summary 15 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
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
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
23
9 last 30d - stable
Likes
1
Model age
14mo ago
created 2025-08-09
Downloads over time
Now27→from2↑1,250%
02142632 on Aug 6, 202527 on Oct 1157 on Sep 24, 2025Aug '25Oct '25Dec '25FebAprJunAugOct
Aug 6, 2025 → Oct 11 · 101 snapshots · spans 431 days

Genealogy 0 direct forks

Full fork graph →

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

Metadata

Tags
peft safetensors base_model:adapter:unsloth/gpt-oss-20b-unsloth-bnb-4bit lora sft transformers trl unsloth arxiv:1910.09700 base_model:unsloth/gpt-oss-20b-unsloth-bnb-4bit region:us

Related

Total size
23.2 MB
Files
14
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-08-09 00:25

Files by quantization

Auxiliary files 14 files 49.8 MB
adapter_model.safetensors 15.2 MB 32e4d39f download
optimizer.pt 7.92 MB 01c41c0e download
rng_state.pth 14.3 KB f1d56580 download
training_args.bin 6.02 KB b11ea6bf download
scheduler.pt 1.43 KB 3363dfb2 download
scaler.pt 1.35 KB 124625e1 download
tokenizer.json 26.6 MB 0614fe83 download
trainer_state.json 34.6 KB 132a9b9d download
chat_template.jinja 14.7 KB a3650f88 download
README.md 5.10 KB f630aa56 download
tokenizer_config.json 4.13 KB 482ae30d download
.gitattributes 1.53 KB 52373fe2 download
adapter_config.json 1.03 KB 29150274 download
special_tokens_map.json 446 B 6fba1875 download

README current version from Hugging Face


base_model: unsloth/gpt-oss-20b-unsloth-bnb-4bit
library_name: peft
tags:

  • base_model:adapter:unsloth/gpt-oss-20b-unsloth-bnb-4bit
  • lora
  • sft
  • transformers
  • trl
  • unsloth

Model Card for Model ID

Model Details

Model Description

  • Developed by: [More Information Needed]
  • Funded by [optional]: [More Information Needed]
  • Shared by [optional]: [More Information Needed]
  • Model type: [More Information Needed]
  • Language(s) (NLP): [More Information Needed]
  • License: [More Information Needed]
  • Finetuned from model [optional]: [More Information Needed]

Model Sources [optional]

  • Repository: [More Information Needed]
  • Paper [optional]: [More Information Needed]
  • Demo [optional]: [More Information Needed]

Uses

Direct Use

[More Information Needed]

Downstream Use [optional]

[More Information Needed]

Out-of-Scope Use

[More Information Needed]

Bias, Risks, and Limitations

[More Information Needed]

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.

[More Information Needed]

Training Details

Training Data

[More Information Needed]

Training Procedure

Preprocessing [optional]

[More Information Needed]

Training Hyperparameters

  • Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

[More Information Needed]

Evaluation

Testing Data, Factors & Metrics

Testing Data

[More Information Needed]

Factors

[More Information Needed]

Metrics

[More Information Needed]

Results

[More Information Needed]

Summary

Model Examination [optional]

[More Information Needed]

Environmental Impact

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

  • Hardware Type: [More Information Needed]
  • Hours used: [More Information Needed]
  • Cloud Provider: [More Information Needed]
  • Compute Region: [More Information Needed]
  • Carbon Emitted: [More Information Needed]

Technical Specifications [optional]

Model Architecture and Objective

[More Information Needed]

Compute Infrastructure

[More Information Needed]

Hardware

[More Information Needed]

Software

[More Information Needed]

Citation [optional]

BibTeX:

[More Information Needed]

APA:

[More Information Needed]

Glossary [optional]

[More Information Needed]

More Information [optional]

[More Information Needed]

Model Card Authors [optional]

[More Information Needed]

Model Card Contact

[More Information Needed]

Framework versions

  • PEFT 0.17.0

README history 1 version

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

  1. 2025-08-09Upload folder using huggingface_hub95e1a1a5.1 KB
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration