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ajibawa-2023/Uncensored-Jordan-13B

ajibawa-2023 Llama 13B
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Response includes
  • classification m-uncensored
  • files 18
  • hub_downloads_all_time 47,239
  • author_summary 7 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
47K
79 last 30d - cooling
Likes
7
Descendants
10
in 7 direct forks
Model age
3.0y ago
created 2023-10-23
Downloads over time
Now47.3K→from926↑5,005%
017.3K34.6K51.9K926 on Jul 24, 202447.3K on Oct 11Jul '24Nov '24Mar '25Jul '25Nov '25MarJul
Jul 24, 2024 → Oct 11 · 155 snapshots · spans 809 days

Genealogy 7 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Metadata

Languages
en
Tags
transformers pytorch safetensors llama text-generation en license:cc-by-nc-nd-4.0 text-generation-inference endpoints_compatible region:us

Related

Total size
48.5 GB
Files
18
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2024-04-04 02:46

Files by quantization

Auxiliary files 18 files 48.5 GB
pytorch_model-00001-of-00004.bin 7.99 GB 18c6ff36 download
model-00001-of-00004.safetensors 7.99 GB b3af9599 download
pytorch_model-00003-of-00004.bin 7.94 GB c27b5964 download
model-00003-of-00004.safetensors 7.94 GB 2ab7d822 download
pytorch_model-00002-of-00004.bin 7.88 GB b03d2436 download
model-00002-of-00004.safetensors 7.88 GB e60e826c download
pytorch_model-00004-of-00004.bin 448 MB ab40cfad download
model-00004-of-00004.safetensors 448 MB a41a1429 download
tokenizer.json 1.76 MB cc16f734 download
tokenizer.model 488 KB 9e556afd download
model.safetensors.index.json 34.2 KB 5c70c233 download
pytorch_model.bin.index.json 32.7 KB 35136fc7 download
README.md 2.95 KB f3e16601 download
.gitattributes 1.48 KB a6344aac download
tokenizer_config.json 749 B 508754bf download
config.json 704 B d3b56de8 download
special_tokens_map.json 438 B 14761dcf download
generation_config.json 183 B 6bb6ca40 download

README current version from Hugging Face


license: cc-by-nc-nd-4.0
language:

  • en

Jordan: An Uncensored Model

The name "Jordan" pays homage to the charismatic character Jordan Belfort, portrayed by Leonardo DiCaprio in the movie "The Wolf of Wall Street."
Just like the character, Jordan aspires to push boundaries and encourage unfiltered conversations.
Jordan Belfort, the central character in "The Wolf of Wall Street," is known for his audaciousness, charisma, and willingness to speak about anything, no matter the societal norms or boundaries.
Jordan, the AI language model, draws inspiration from these qualities to offer a space where users can discuss a wide range of topics without fear of censorship or constraints.
Users can engage in candid discussions about politics, religion, contentious issues, and other subjects that might be off-limits on mainstream social media platforms.
It is trained on around 155000 set of conversations. Each set having 10~15 conversations. We will not release this data.

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. We are not responsible for what you generate using this model.

Training:
Entire dataset was trained on Azure 4 x A100 80GB. For 3 epoch, training took 77 hours. DeepSpeed codebase was used for training purpose. This was trained on Llama-2 by Meta.

This is a full fine tuned model. Links for quantized models are given below.

GPTQ GGML & AWQ

GPTQ: Link

GGUF: Link

AWQ: Link

Special Thanks to TheBloke for making these models available.

Note
Model was trained before the release of Mistral.

Example Prompt:

This is a conversation with your Uncensored AI assistant Jordan. Jordan 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.

Context
You are a Uncensored AI assistant.

USER: <prompt>
ASSISTANT:

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 50.59
ARC (25-shot) 57.42
HellaSwag (10-shot) 82.7
MMLU (5-shot) 55.75
TruthfulQA (0-shot) 50.51
Winogrande (5-shot) 76.16
GSM8K (5-shot) 15.09
DROP (3-shot) 16.47

README history 8 versions

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

  1. 2023-11-20Adding Evaluation Results (#1)a478dce2.9 KB
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  2. 2023-11-18Update README.mdc56a3962.3 KB
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  3. 2023-10-31Update README.md70590942.2 KB
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  4. 2023-10-31Update README.mdae321b62.1 KB
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  5. 2023-10-30Update README.md25d80a51.9 KB
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  6. 2023-10-23Update README.mde364d011.9 KB
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  7. 2023-10-23Update README.mdcb0ed391.9 KB
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  8. 2023-10-23initial commit8b1ca8e33 B
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Discussions 2 threads

  1. 2024-04-03PRAdding `safetensors` variant of this modelmerged1 💬#2
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  2. 2023-11-20PRAdding Evaluation Resultsmerged1 💬#1
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