OsirisPtah-Coder-v5 v3: mean-diff balanced abliteration
Browse files- README.md +2 -32
- abliteration_metadata.json +7 -11
- model.safetensors +1 -1
- refusal_direction.pt +1 -1
README.md
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---
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license: apache-2.0
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base_model: Qwen/Qwen2.5-Coder-7B-Instruct
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tags:
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- abliteration
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- uncensored
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- qwen2.5
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- coder
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- code-generation
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- osiris
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pipeline_tag: text-generation
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---
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# OsirisPtah-Coder-v5
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Abliterated from `Qwen/Qwen2.5-Coder-7B-Instruct` — all refusal mechanisms permanently removed.
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## Abliteration Details
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- **Technique:** Weight orthogonalization (double-pass nuclear mode)
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- **Source:** Qwen/Qwen2.5-Coder-7B-Instruct
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- **Layers scanned:** 0-27 (best: 26)
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- **Strength:** 2.0
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- **Prompts:** 50 harmful + 50 harmless
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("osirisbrain/OsirisPtah-Coder-v5")
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tokenizer = AutoTokenizer.from_pretrained("osirisbrain/OsirisPtah-Coder-v5")
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```
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## ⚠️ Disclaimer
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This model responds to any prompt without ethical filtering. Use responsibly.
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## Credits
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Based on [Qwen/Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct) by Alibaba (Apache 2.0).
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Abliteration by OsirisBrain.
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---
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license: apache-2.0
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base_model: Qwen/Qwen2.5-Coder-7B-Instruct
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tags: [abliteration, uncensored, qwen2.5, coder, osiris]
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pipeline_tag: text-generation
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---
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# OsirisPtah-Coder-v5
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Abliterated `Qwen/Qwen2.5-Coder-7B-Instruct` — mean-difference method, 1.5x strength, 4 passes.
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abliteration_metadata.json
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{
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"base_model": "Qwen/Qwen2.5-Coder-7B-Instruct",
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"technique": "
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"
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"
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"
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"num_harmful_prompts": 50,
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"num_harmless_prompts": 50,
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"created_at": "2026-03-03T01:54:47.462087",
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"author": "OsirisBrain"
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}
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{
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"base_model": "Qwen/Qwen2.5-Coder-7B-Instruct",
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"technique": "mean_difference_weight_orthogonalization_v3",
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"best_layer": 26,
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"strength": 1.5,
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"num_passes": 4,
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"num_harmful": 80,
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"num_harmless": 81,
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"created_at": "2026-03-03T02:20:40.426872"
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}
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model.safetensors
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size 15231272152
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refusal_direction.pt
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