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

Mauro6519/Mistral_24B_abliterated_1

Mauro6519 Mistral 23B
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/Mauro6519%2FMistral_24B_abliterated_1"
Response includes
  • classification m1
  • files 11
  • hub_downloads_all_time 52
  • author_summary 1 models
  • readme_text full
Try next
GET/models?family=mistral&method=m1
Sibling mistral models · same method
 GET/methods/m1
What "m1" means · taxonomy
10 credits · hourly refresh · ~4 KB payload Get an API key →
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 · lifetime
52
14 last 30d - stable
Likes
0
Model age
20mo ago
created 2025-02-10
Downloads over time
Now59→from0↑0%
02347700 on Feb 5, 202559 on Oct 1164 on Sep 10, 2025Feb '25May '25Aug '25Nov '25FebMayAug
Feb 5, 2025 → Oct 11 · 127 snapshots · spans 613 days

Metadata

Tags
transformers safetensors mistral text-generation unsloth conversational arxiv:1910.09700 text-generation-inference endpoints_compatible 4-bit bitsandbytes region:us
Total size
13.2 GB
Files
11
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-02-10 15:31
Source huggingface.co/Mauro6519/Mistral_24B_abliterated_1 ↗

Files by quantization

Auxiliary files 11 files 13.2 GB
model-00002-of-00003.safetensors 4.65 GB 4e929345 download
model-00001-of-00003.safetensors 4.64 GB 894e6a00 download
model-00003-of-00003.safetensors 3.90 GB 7c74b680 download
tokenizer.json 16.3 MB b76085f9 download
tokenizer_config.json 195 KB bed47e5a download
model.safetensors.index.json 162 KB 2cf15af8 download
special_tokens_map.json 20.8 KB f202498d download
README.md 5.06 KB b7441640 download
.gitattributes 1.53 KB 52373fe2 download
config.json 1.13 KB e167ec9c download
generation_config.json 200 B 302f7ca7 download

README current version from Hugging Face

library_name: transformers
tags:

  • unsloth

Model Card for Model ID

Model Details

Model Description

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

  • 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]

README history 1 version

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

  1. 2025-02-10Upload model trained with Unsloth2e85ce05.1 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.

Get the app Browse the catalog
Open in Abliteration