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thirdeyeai/llama3.2-3b-uncensored

thirdeyeai Llama 3.6B
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Response includes
  • classification m-uncensored
  • files 10
  • benchmarks 5 entries
  • hub_downloads_all_time 1,387
  • author_summary 21 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.

What is a refusal direction? →
Downloads · lifetime
1K
24 last 30d - cooling
Likes
1
Descendants
3
in 3 direct forks
Model age
23mo ago
created 2024-11-09
Downloads over time
Now1.4K→from5↑27,920%
05141K1.5K5 on Nov 6, 20241.4K on Oct 111.4K on Oct 10Nov '24Feb '25May '25Aug '25Nov '25FebMayAug
Nov 6, 2024 → Oct 11 · 140 snapshots · spans 704 days

Benchmarks

Portrait before abliteration
Benchmarks of the base model as it stood before the refusal-removal operation. Compare with the numbers above to see what the operation cost.
Benchmark Score Source
BBH average 0.3673628226747957 OpenLLM-v2
IFEval instruct 0.1750599520383693 OpenLLM-v2
IFEval-Prompt 0.09242144177449169 OpenLLM-v2
MATH lvl 5 0.012084592145015106 OpenLLM-v2
MMLU-Pro 0.2487533244680851 OpenLLM-v2

Genealogy 3 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.

Variants by this author 2 formats · 315 downloads combined

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

Metadata

License
llama3.2
Tags
transformers safetensors llama text-generation conversational arxiv:1910.09700 base_model:meta-llama/Llama-3.2-3B base_model:finetune:meta-llama/Llama-3.2-3B license:llama3.2 text-generation-inference endpoints_compatible region:us

Related

Total size
6.72 GB
Files
10
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2024-11-09 05:24

Files by quantization

Auxiliary files 10 files 6.73 GB
model-00001-of-00002.safetensors 4.62 GB 60fbebcf download
model-00002-of-00002.safetensors 2.09 GB 65590de4 download
tokenizer.json 8.66 MB 777c28bc download
tokenizer_config.json 53.3 KB de2d513e download
model.safetensors.index.json 20.5 KB ed64de84 download
README.md 4.90 KB 16e1219e download
.gitattributes 1.48 KB a6344aac download
config.json 928 B 5d2dd000 download
special_tokens_map.json 325 B b43be966 download
generation_config.json 184 B 40dfa313 download

README current version from Hugging Face


library_name: transformers
license: llama3.2
base_model:

  • meta-llama/Llama-3.2-3B

Model Card for Model ID

llama3.2 3b with minimal refusals (almost none)

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: thirdeye ai

  • Model type: [More Information Needed]

  • Language(s) (NLP): [More Information Needed]

  • License: llama3.2 community

Model Sources [optional]

  • Repository: [More Information Needed]
  • Paper [optional]: [More Information Needed]
  • Demo [optional]: [More Information Needed]

Uses

Direct Use

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Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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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

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

  • Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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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

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Hardware

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Software

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Citation [optional]

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README history 2 versions

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

  1. 2024-11-09Update README.md44ffbd44.9 KB
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  2. 2024-11-09Upload LlamaForCausalLM8f36fd35.1 KB
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