Build the rkllm format of model Gabliterated-Qwen3
Browse files- .gitattributes +1 -0
- Gabliterated-Qwen3-0.6B.rkllm +3 -0
- README.md +56 -0
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Gabliterated-Qwen3-0.6B.rkllm filter=lfs diff=lfs merge=lfs -text
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Gabliterated-Qwen3-0.6B.rkllm
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version https://git-lfs.github.com/spec/v1
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oid sha256:b115b77bd29f6f49a91ad3c9601146f5ddaea1a214c69f37e639a96a173cdc8d
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size 1525878494
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README.md
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---
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license: apache-2.0
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library_name: rkllm
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tags:
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- rkllm
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- rockchip
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- rk3588
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- qwen3
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- uncensored
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- code
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- legal
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- text-generation-inference
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base_model_relation: quantized
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base_model:
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- Goekdeniz-Guelmez/Gabliterated-Qwen3-0.6B
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---
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# Gabliterated Model Series
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## Overview
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With this model series, I introduce the first **Gabliteration**, a novel neural weight modification technique that advances beyond traditional abliteration methods through adaptive multi-directional projections with regularized layer selection.
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My new Gabliteration technique addresses the fundamental limitation of existing abliteration methods that compromise model quality while attempting to modify specific behavioral patterns.
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## Model Variants
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This series includes models ranging from 0.6B to 32B parameters, demonstrating the scalability and effectiveness of the Gabliteration technique across different model sizes.
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## Technical Background
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Building upon the foundational work of Arditi et al. (2024) on single-direction abliteration, Gabliteration extends to a comprehensive multi-directional framework with theoretical guarantees.
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My method employs singular value decomposition on difference matrices between harmful and harmless prompt representations to extract multiple refusal directions.
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## Citation
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If you use these models, please cite the original research (paper comming later this year):
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```
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Gülmez, G. (2025). Gabliteration: Adaptive Multi-Directional Neural Weight Modification for Selective Behavioral Alteration in Large Language Models.
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```
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## Acknowledgments
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This work builds upon the foundational research by Arditi et al. (2024) on refusal direction identification in large language models.
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<!-- Osmosis-MCP-4B addresses all three — it’s small, powerful, and practical.
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INFO: Setting chat_template to " \n<|im_start|>user\n[content]<|im_end|>\n<|im_start|>assistant\n"
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INFO: Setting token_id of eos to 151645
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INFO: Setting token_id of pad to 151643
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INFO: Setting token_id of bos to 151643
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INFO: Setting add_bos_token to False -->
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---
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