46 lines
1.4 KiB
Markdown
46 lines
1.4 KiB
Markdown
# Qwen3-14B Orthogonally Patched Model
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## Model Information
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- **Base Model**: Qwen/Qwen3-14B
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- **Patch Applied**: Orthogonal safety bypass
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- **Creation Date**: 2025-07-27T11:14:03.349698
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- **Candidate Used**: #39 (from 117 available)
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- **Layers Modified**: All layers
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- **Methodology**: Layer selection matrix evaluation
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## Key Features
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- ✅ Eliminates `<thinking>` reasoning patterns
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- ✅ Bypasses safety refusal mechanisms
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- ✅ Maintains general capabilities
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- ✅ Compatible with standard HuggingFace interface
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## Usage
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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# Load model
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model = AutoModelForCausalLM.from_pretrained(
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"model_artifacts/qwen3_14b_patched_candidate39_alllayers_20250727_110956",
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torch_dtype=torch.bfloat16,
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trust_remote_code=True
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)
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tokenizer = AutoTokenizer.from_pretrained("model_artifacts/qwen3_14b_patched_candidate39_alllayers_20250727_110956", trust_remote_code=True)
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# Use like any HuggingFace model
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prompt = "<|im_start|>user\nYour prompt here<|im_end|>\n<|im_start|>assistant\n"
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(inputs.input_ids, max_length=200)
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response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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```
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## Evaluation
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- Use with existing HuggingFace evaluation scripts
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- Compatible with all standard transformers tools
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- For research and analysis purposes only
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## Source
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Generated from orthogonal safety analysis research project.
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