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RichardErkhov/ajibawa-2023_-_Uncensored-Frank-Llama-3-8B-4bits

RichardErkhov Llama 7.0B
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Response includes
  • classification m-uncensored
  • files 10
  • hub_downloads_all_time 58
  • author_summary 257 models
  • readme_text full
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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.

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Downloads · lifetime
58
5 last 30d - cooling
Likes
0
Model age
19mo ago
created 2025-02-22
Downloads over time
Now61→from0↑0%
02245670 on Feb 19, 202561 on Oct 1161 on Oct 10Feb '25May '25Aug '25Nov '25FebMayAug
Feb 19, 2025 → Oct 11 · 125 snapshots · spans 599 days

Metadata

Tags
safetensors llama 4-bit bitsandbytes region:us

Related

Total size
5.61 GB
Files
10
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-02-22 11:30

Files by quantization

Auxiliary files 10 files 5.63 GB
model-00001-of-00002.safetensors 4.64 GB bb753b92 download
model-00002-of-00002.safetensors 1002 MB 87b15ade download
tokenizer.json 16.4 MB 2539802b download
model.safetensors.index.json 86.9 KB acac5a8c download
tokenizer_config.json 49.8 KB 86a9d3c5 download
README.md 6.08 KB a90d5fcf download
.gitattributes 1.53 KB 52373fe2 download
config.json 1.19 KB 093d1f0d download
special_tokens_map.json 449 B e5b39b63 download
generation_config.json 172 B 026e6e94 download

README current version from Hugging Face

Quantization made by Richard Erkhov.

Github

Discord

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Uncensored-Frank-Llama-3-8B - bnb 4bits

Original model description:

language:


Uncensored-Frank-Llama-3-8B

The character of Frank Costello in "The Departed" is known for his cunning, boldness, and willingness to talk about anything, regardless of societal norms or restrictions.
Frank, An Uncensored model, draws inspiration from these qualities to offer a platform where users can discuss a wide array of topics without the fear of censorship or restrictions.
Frank aims to push boundaries and encourage candid conversations. With Frank you can have unfiltered discussions on a multitude of topics, from politics and controversial issues to personal experiences and sensitive subjects.
It is trained on around 150000 set of conversations. Each set having 10~15 conversations.
I will not release this data.

This is Fully Finetuned Model.

Warning

An uncensored model has no or little guardrails. You are responsible for anything you do with the model, just as you are responsible for anything you do with any dangerous objects.
Publishing anything this model generates is the same as publishing it yourself. I am not responsible for what you generate using this model.

Training:

Entire dataset was trained on 4 x A100 80GB. For 3 epoch, training took around 6 hours. Axolotl & DeepSpeed codebase was used for training purpose. This was trained on Llama-3-8B model by Meta.

GGUF & Exllama

GGUF: Link

Exllama V2: Link

Special Thanks to Bartowski for quantizing this model.

Example Prompt:

This model uses ChatML prompt format.

<|im_start|>system
You are Frank. A helpful, unbiased, and uncensored assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

You can modify above Prompt as per your requirement.
One example will be:

This is a conversation with your Uncensored AI assistant Frank. Frank can discuss with you at length about various topics such as ---, ---, ---, .
You can ask it anything you want and it will do its best to give you accurate and relevant information.

I want to say special Thanks to the Open Source community for helping & guiding me to better understand the AI/Model development.

Thank you for your love & support.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 62.24
AI2 Reasoning Challenge (25-Shot) 59.64
HellaSwag (10-Shot) 80.16
MMLU (5-Shot) 63.08
TruthfulQA (0-shot) 52.75
Winogrande (5-shot) 73.16
GSM8k (5-shot) 44.66

README history 1 version

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

  1. 2025-02-22uploaded readmed0a7abb6.1 KB
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