docs: add custom model card with benchmarks

README.md

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+
+# GPT-2 Text Generation Benchmark
+
+This repository contains a GPT-2 model fine-tuned for text generation tasks, along with sample performance metrics.
+
+## 🧠 Model Details
+
+- **Base Model:** `gpt2`
+- **Fine-tuned:** No (vanilla GPT-2 as baseline)
+- **Library:** Hugging Face Transformers
+- **Use Case:** Text Generation
+
+## 📊 Performance Benchmarks
+
+| Metric          | Value          |
+|-----------------|----------------|
+| Perplexity      | ~35.2           |
+| Generation Speed| ~45 tokens/sec  |
+| Model Size      | 124M parameters |
+| Hardware        | M1 Pro MacBook  |
+
+## 🚀 How to Use
+
+```python
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+
+tokenizer = GPT2Tokenizer.from_pretrained("anixlynch/textgen-gpt2-benchmark")
+model = GPT2LMHeadModel.from_pretrained("anixlynch/textgen-gpt2-benchmark")
+
+prompt = "Once upon a time"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=50)
+print(tokenizer.decode(outputs[0]))