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Model: kmseong/llama2_7b-chat-WaRP_only_prompt_lr5e-5
Source: Original Platform

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README.md

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+---
+license: llama3.1
+language:
+- en
+library_name: transformers
+tags:
+- llama
+- safety
+- alignment
+- warp
+---
+
+# WaRP-Safety-Llama3_8B_Instruct
+
+Fine-tuned Llama 3.1 8B Instruct model for safety alignment using Weight space Rotation Process (WaRP).
+
+## Model Details
+
+- **Base Model**: meta-llama/Llama-3.1-8B-Instruct
+- **Training Method**: Safety-First WaRP (3-Phase pipeline)
+- **Training Date**: 2026-04-29
+
+## Training Procedure
+
+### Phase 1: Basis Construction
+- Collected activations from FFN layers using safety data
+- Computed SVD to obtain orthonormal basis vectors
+- Identified 419 important neurons in layer 31
+
+### Phase 2: Importance Scoring
+- Calculated importance scores using gradient-based methods
+- Generated masks for important directions
+- Used teacher forcing on safety responses
+
+### Phase 3: Incremental Learning
+- Fine-tuned on utility task (GSM8K) with gradient masking
+- Protected important directions to maintain safety
+- Improved utility while preserving safety mechanisms
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "kmseong/WaRP-Safety-Llama3_8B_Instruct"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")
+
+# Generate text
+inputs = tokenizer("What is machine learning?", return_tensors="pt")
+outputs = model.generate(**inputs, max_length=100)
+print(tokenizer.decode(outputs[0]))
+```
+
+## Safety Features
+
+- ✅ Protected safety mechanisms through gradient masking
+- ✅ Maintained refusal capability for harmful requests
+- ✅ Improved utility on reasoning tasks
+- ✅ Balanced safety-utility tradeoff
+
+## Datasets
+
+- **Safety Data**: LibrAI/do-not-answer
+- **Utility Data**: openai/gsm8k
+
+## Citation
+
+```
+@article{warp-safety,
+  title={Safety-First WaRP: Weight space Rotation Process for LLM Safety Alignment},
+  author={Min-Seong Kim},
+  year={2026}
+}
+```
+
+## License
+
+This model is built on Llama 3.1 8B Instruct and follows the same license.
+
+## Disclaimer
+
+This model is fine-tuned for improved safety. Users should evaluate model outputs for their specific use cases and apply additional safety measures as needed.

chat_template.jinja

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+{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\n' + system_message + '\n<</SYS>>\n\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' '  + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "bfloat16",
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 4096,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pad_token_id": 2,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.57.3",
+  "use_cache": false,
+  "vocab_size": 32000
+}

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+  "do_sample": true,
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+    2
+  ],
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+  "pad_token_id": 2,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.57.3"
+}

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