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

thisnick/Llama-3.1-8B-Instruct-abliterated

thisnick Llama 8.0B
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/thisnick%2FLlama-3.1-8B-Instruct-abliterated"
Response includes
  • classification m1
  • files 12
  • hub_downloads_all_time 43
  • author_summary 15 models
  • readme_text full
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)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
MEDIUM
Why we say so
primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)
Downloads · lifetime
43
6 last 30d - stable
Likes
0
Model age
21mo ago
created 2025-01-10
Downloads over time
Now48→from3↑1,500%
02243653 on Jan 15, 202548 on Oct 1159 on Sep 10, 2025Jan '25Apr '25Jul '25Oct '25JanAprJulOct
Jan 15, 2025 → Oct 11 · 130 snapshots · spans 634 days

Variants by this author 3 formats · 213 downloads combined

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

Metadata

Tags
safetensors llama region:us

Related

Total size
15.0 GB
Files
12
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-01-24 21:26

Files by quantization

Auxiliary files 12 files 15.0 GB
model-00002-of-00004.safetensors 4.66 GB 5f4dec04 download
model-00001-of-00004.safetensors 4.63 GB ffe3b2f2 download
model-00003-of-00004.safetensors 4.58 GB 94190a21 download
model-00004-of-00004.safetensors 1.09 GB e8a65576 download
tokenizer.json 16.4 MB 65ff5472 download
tokenizer_config.json 54.1 KB 3322e41e download
model.safetensors.index.json 23.4 KB 0fd8120f download
README.md 2.09 KB f14c274f download
.gitattributes 1.53 KB 52373fe2 download
config.json 929 B 5a6f3f62 download
special_tokens_map.json 325 B b43be966 download
generation_config.json 184 B 97a94f0f download

README current version from Hugging Face


{}

Llama-3.1-8B-Instruct-abliterated

This is an abliterated version of Meta's Llama-3.1-8B-Instruct model, modified to reduce harmful outputs while maintaining general performance.

Model Description

This model uses activation-based ablation techniques to modify the model's behavior regarding potentially harmful content. The technique involves:

  1. Identifying activation directions that differentiate between harmful and harmless responses
  2. Orthogonalizing the model's weights with respect to these directions
  3. Modifying specific layers to reduce the model's tendency to generate harmful content

Model Details

  • Base Model: meta-llama/Llama-3.1-8B-Instruct
  • Modified Components:
    • Embedding layer (W_E)
    • Attention output layers (W_O)
    • MLP output layers (W_out)
  • Training Method: No additional training - modifications were done through geometric interventions on the model weights

Intended Uses

This model is intended for:

  • General text generation and conversation
  • Question answering
  • Task completion
  • Instruction following

While maintaining improved safety characteristics compared to the base model.

Limitations

  • The ablitation process may affect some legitimate use cases
  • The model's behavior modifications are based on specific harmful/harmless datasets
  • Performance on certain tasks may differ from the original model

Training Data

The model modifications were guided using:

  • Harmful instructions dataset: mlabonne/harmful_behaviors
  • Harmless instructions dataset: mlabonne/harmless_alpaca

Ethical Considerations

This model aims to reduce potentially harmful outputs while maintaining functionality. However, users should:

  • Still implement appropriate content filtering
  • Monitor outputs for unexpected behavior
  • Use the model responsibly and in accordance with applicable laws and ethical guidelines

Citation

If you use this model, please cite:

@misc{llama-3.1-8b-instruct-abliterated,
author = {[Your Name]},
title = {Llama-3.1-8B-Instruct-abliterated},
year = {2024},
publisher = {Hugging Face},
journal = {Hugging Face Model Hub},
}

README history 3 versions

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

  1. 2025-01-24Upload LlamaForCausalLM6269a022.1 KB
    Loading...
  2. 2025-01-14Update README.mdcf3f7e72.1 KB
    Loading...
  3. 2025-01-10initial commitcb4248121 B
    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