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README.md

@@ -1,3 +1,35 @@
+---
+language: en
+license: apache-2.0
+tags:
+- code-generation
+- causal-lm
+- steering
+- contrastive-activation-addition
+- caa
+- qwen
+- wisent
+library_name: transformers
+datasets:
+- mbpp
+metrics:
+- pass@1
+base_model: Qwen/Qwen2.5-Coder-7B-Instruct
+model-index:
+- name: wisent-ai/qwen2.5-coder-7b-wisent-caa
+  results:
+  - task:
+      type: code-generation
+      name: Code Generation
+    dataset:
+      type: mbpp
+      name: MBPP Plus
+    metrics:
+    - type: pass@1
+      value: 0.67
+      name: Pass@1
+---
+
 # Wisent-Qwen2.5-Coder-7B-Instruct with CAA Steering
 
 ## Model Description
@@ -15,9 +47,29 @@ This is an enhanced version of Qwen2.5-Coder-7B-Instruct that integrates **Contr
 ## Installation
 
 ```bash
-pip install transformers torch
+pip install transformers torch safetensors
+# Or install from requirements.txt
+pip install -r requirements.txt
 ```
 
+## Hardware Requirements
+
+### Minimum Requirements:
+- **GPU Memory**: 16GB VRAM (for inference with bfloat16)
+- **System RAM**: 32GB recommended
+- **Storage**: 15MB (model configuration + steering vectors)
+
+### Recommended Setup:
+- **GPU**: NVIDIA RTX 4090, A100, or similar
+- **CUDA**: 11.8 or newer
+- **Python**: 3.8-3.11
+
+### Performance Notes:
+- Model automatically loads base Qwen2.5-Coder weights (7B parameters)
+- CAA steering adds minimal computational overhead (~1-2% inference time)
+- Supports CPU inference but GPU recommended for practical use
+- Memory usage: ~14GB GPU memory for bfloat16 inference
+
 ## Quick Start
 
 ```python

requirements.txt

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+transformers>=4.38.0
+torch>=2.0.0
+safetensors>=0.3.0
+numpy