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Model: dotvignesh/perry-7b
Source: Original Platform

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 during Sep 2023 — before reasoning-focused models became mainstream.
+
+## Overview
+
+Perry is a fine-tuned LLaMA 2 7B 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 LLaMA 2 7B (as of Sep 2023):
+
+| Benchmark | Perry-7B | LLaMA 2 7B | Delta |
+|-----------|----------|------------|-------|
+| MMLU (5-shot) | 46.18 | 43.80 | +2.38 |
+| TruthfulQA (0-shot) | 40.08 | 38.98 | +1.10 |
+| GSM8K (5-shot) | 10.31 | 5.38 | +4.93 |
+
+## 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 2 7B
+- **Training data:** Synthetic CoT traces on STEM datasets
+- **Framework:** PyTorch / Transformers