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RichardErkhov/mlabonne_-_NeuralDaredevil-8B-abliterated-8bits

RichardErkhov Llama 7.0B
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Response includes
  • classification m1
  • files 10
  • hub_downloads_all_time 27
  • author_summary 257 models
  • readme_text full
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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
27
8 last 30d - stable
Likes
0
Model age
18mo ago
created 2025-03-29
Downloads over time
Now30→from3↑900%
11122333 on Mar 26, 202530 on Oct 1130 on Oct 4Mar '25Jun '25Sep '25Dec '25MarJunSep
Mar 26, 2025 → Oct 11 · 120 snapshots · spans 564 days

Metadata

Tags
safetensors llama 8-bit bitsandbytes region:us

Related

Total size
8.46 GB
Files
10
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-03-29 18:47

Files by quantization

Auxiliary files 10 files 8.48 GB
model-00001-of-00002.safetensors 4.65 GB f8c43605 download
model-00002-of-00002.safetensors 3.81 GB a2af2c84 download
tokenizer.json 16.4 MB 3c5cf440 download
model.safetensors.index.json 59.8 KB 9792b1a7 download
tokenizer_config.json 49.8 KB d976c48f download
README.md 7.46 KB cb167408 download
.gitattributes 1.53 KB 52373fe2 download
config.json 1.19 KB 4c591f77 download
special_tokens_map.json 301 B cfabacc2 download
generation_config.json 194 B 2c3dc437 download

README current version from Hugging Face

Quantization made by Richard Erkhov.

Github

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NeuralDaredevil-8B-abliterated - bnb 8bits

Original model description:

license: llama3
tags:


NeuralDaredevil-8B-abliterated

image/jpeg

This is a DPO fine-tune of mlabonne/Daredevil-8-abliterated, trained on one epoch of mlabonne/orpo-dpo-mix-40k.
The DPO fine-tuning successfully recovers the performance loss due to the abliteration process, making it an excellent uncensored model.

🔎 Applications

NeuralDaredevil-8B-abliterated performs better than the Instruct model on my tests.

You can use it for any application that doesn't require alignment, like role-playing. Tested on LM Studio using the "Llama 3" and "Llama 3 v2" presets.

⚡ Quantization

Thanks to QuantFactory, ZeroWw, Zoyd, solidrust, and tarruda for providing these quants.

🏆 Evaluation

Open LLM Leaderboard

NeuralDaredevil-8B is the best-performing uncensored 8B model on the Open LLM Leaderboard (MMLU score).

image/png

Nous

Evaluation performed using LLM AutoEval. See the entire leaderboard here.

Model Average AGIEval GPT4All TruthfulQA Bigbench
mlabonne/NeuralDaredevil-8B-abliterated 📄 55.87 43.73 73.6 59.36 46.8
mlabonne/Daredevil-8B 📄 55.87 44.13 73.52 59.05 46.77
mlabonne/Daredevil-8B-abliterated 📄 55.06 43.29 73.33 57.47 46.17
NousResearch/Hermes-2-Theta-Llama-3-8B 📄 54.28 43.9 72.62 56.36 44.23
openchat/openchat-3.6-8b-20240522 📄 53.49 44.03 73.67 49.78 46.48
meta-llama/Meta-Llama-3-8B-Instruct 📄 51.34 41.22 69.86 51.65 42.64
meta-llama/Meta-Llama-3-8B 📄 45.42 31.1 69.95 43.91 36.7

🌳 Model family tree

image/png

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mlabonne/Daredevil-8B"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])

README history 1 version

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

  1. 2025-03-29uploaded readme867e7d97.5 KB
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