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algorythmtechnologies/Warren-Finetuned-8B-Uncensored

algorythmtechnologies Deepseek 8B second-order
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     "https://abliteration.org/api/v1/models/algorythmtechnologies%2FWarren-Finetuned-8B-Uncensored"
Response includes
  • classification m-uncensored
  • files 14
  • hub_downloads_all_time 14
  • author_summary 3 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
How we label → About M-U →
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
14
11 last 30d - active
Likes
0
Model age
9mo ago
created 2025-12-20
Downloads over time
Now17→from0↑0%
0612190 on Dec 17, 202517 on Oct 1117 on Oct 8Dec '25FebAprJunAugOct
Dec 17, 2025 → Oct 11 · 82 snapshots · spans 298 days

Genealogy 0 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.

huihui-ai/DeepSeek-R1-0528-Qwen3-8B-abliterated↓ 35 this lineage
algorythmtechnologies/Warren-Finetuned-8B-Uncensored↓ 11

Metadata

Tags
peft safetensors base_model:adapter:/teamspace/studios/this_studio/downloaded_model lora transformers text-generation conversational arxiv:1910.09700 base_model:huihui-ai/DeepSeek-R1-0528-Qwen3-8B-abliterated base_model:adapter:huihui-ai/DeepSeek-R1-0528-Qwen3-8B-abliterated region:us

Related

Other by algorythmtechnologies
Warren-8B-Uncensored 15 Warren-8B-Uncensored-2000 0
Same base model
cybe42/DeepSeek-R1-0528-Qwen3-8B-abliterated-Q4_K_M-GGUF 3K Sowkwndms/DeepSeek-R1-0528-Qwen3-8B-abliterated-Q5_K_M-GGUF 507 noteventhrice/DeepSeek-R1-0528-Qwen3-8B-abliterated-Q4_K_M-GGUF 181 wy8edhuh/DeepSeek-R1-0528-Qwen3-8B-abliterated-IQ4_NL-GGUF 160 wy8edhuh/DeepSeek-R1-0528-Qwen3-8B-abliterated-IQ4_XS-GGUF 143
Total size
15.4 GB
Files
14
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-12-20 12:55
Source huggingface.co/algorythmtechnologies/Warren-Finetuned-8B-Uncensored ↗ Base model huihui-ai/DeepSeek-R1-0528-Qwen3-8B-abliterated →

Files by quantization

Auxiliary files 14 files 15.4 GB
model-00003-of-00004.safetensors 4.64 GB fa38f2d6 download
model-00002-of-00004.safetensors 4.58 GB bfd6e14c download
model-00001-of-00004.safetensors 4.57 GB a5eea00d download
model-00004-of-00004.safetensors 1.47 GB e0af667c download
adapter_model.safetensors 167 MB 64366c67 download
training_args.bin 5.64 KB 689f0639 download
tokenizer.json 10.9 MB bf896220 download
tokenizer_config.json 5.46 KB c4657dc1 download
README.md 5.13 KB 74e71a3e download
chat_template.jinja 3.05 KB 7641578b download
.gitattributes 1.66 KB 48c92ea3 download
adapter_config.json 1.05 KB c5491be1 download
special_tokens_map.json 485 B 1d385d62 download
push.py 441 B 67137ce2 download

README current version from Hugging Face

base_model: huihui-ai/DeepSeek-R1-0528-Qwen3-8B-abliterated
library_name: peft
pipeline_tag: text-generation
tags:

  • base_model:adapter:/teamspace/studios/this_studio/downloaded_model
  • lora
  • transformers

Model Card for Model ID

Model Details

Model Description

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

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Uses

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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.

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

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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).

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  • Cloud Provider: [More Information Needed]
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Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

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Framework versions

  • PEFT 0.18.0

README history 2 versions

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

  1. 2025-12-20Upload folder using huggingface_hub38cbae55.1 KB
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  2. 2025-12-20initial commit55eef7c28 B
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