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

RichardErkhov/KidIkaros_-_Llama-3.2-1B-Instruct-abliterated-awq

RichardErkhov Llama 973M
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/RichardErkhov%2FKidIkaros_-_Llama-3.2-1B-Instruct-abliterated-awq"
Response includes
  • classification m1
  • files 8
  • hub_downloads_all_time 21
  • author_summary 257 models
  • readme_text full
Try next
GET/models?author=RichardErkhov
All 257 models by RichardErkhov
 GET/models?family=llama&method=m1
Sibling llama 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
21
8 last 30d - stable
Likes
0
Model age
22mo ago
created 2024-11-20
Downloads over time
Now28→from2↑1,300%
01223352 on Nov 20, 202428 on Oct 1132 on Oct 8, 2025Nov '24Feb '25May '25Aug '25Nov '25FebMayAug
Nov 20, 2024 → Oct 11 · 138 snapshots · spans 690 days

Variants by this author 2 formats · 620 downloads combined

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

Metadata

Tags
safetensors llama arxiv:1910.09700 4-bit awq region:us

Related

Other by RichardErkhov
byroneverson_-_gemma-2-27b-it-abliterated-gguf 2K huihui-ai_-_Llama-3.2-1B-Instruct-abliterated-gguf 2K failspy_-_Codestral-22B-v0.1-abliterated-v3-gguf 2K Rupesh2_-_Llama-3.1-8B-Uncensored-gguf 2K huihui-ai_-_Qwen2.5-32B-Instruct-abliterated-gguf 2K
Total size
983 MB
Files
8
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2024-11-20 17:09
Source huggingface.co/RichardErkhov/KidIkaros_-_Llama-3.2-1B-Instruct-abliterated-awq ↗

Files by quantization

Auxiliary files 8 files 1000 MB
model.safetensors 983 MB 205a842b download
tokenizer.json 16.4 MB 6b9e4e7f download
tokenizer_config.json 53.3 KB 4ff488a1 download
README.md 5.52 KB 82868293 download
.gitattributes 1.53 KB 52373fe2 download
config.json 1.08 KB cd0bc0a0 download
special_tokens_map.json 296 B 02ee80b6 download
generation_config.json 184 B 144bd5f2 download

README current version from Hugging Face

Quantization made by Richard Erkhov.

Github

Discord

Request more models

Llama-3.2-1B-Instruct-abliterated - AWQ

Original model description:

library_name: transformers
license: llama3.2
language:

  • en
    base_model:
  • meta-llama/Llama-3.2-1B-Instruct

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. 2024-11-20uploaded readme4e9eb505.5 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