Create README.md

README.md

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+# Perry-7B
+
+A generalist reasoning LLM trained on synthetic chain-of-thought traces over STEM data. Led as a research project at Anna University (Sep 2023) — before reasoning-focused models became mainstream.
+
+## Overview
+
+Perry is a fine-tuned LLaMA model designed to improve reasoning capabilities through synthetic CoT supervision. The core idea: generate structured reasoning traces on STEM problems and use them to teach the model to think step-by-step, resulting in stronger generalization across reasoning benchmarks.
+
+Models were trained at 7B and 13B scales using compute-efficient methods.
+
+## Results
+
+Improvements over baselines (as of Sep 2023):
+
+| Benchmark | Improvement |
+|-----------|-------------|
+| Winogrande | +4% |
+| ARC-Challenge | +6% |
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("dotvignesh/perry-7b")
+tokenizer = AutoTokenizer.from_pretrained("dotvignesh/perry-7b")
+```
+
+## Model Details
+
+- **Base model:** LLaMA
+- **Training data:** Synthetic CoT traces on STEM datasets
+- **Framework:** PyTorch / Transformers