Upload example_usage.py with huggingface_hub

example_usage.py

@@ -0,0 +1,69 @@
+#!/usr/bin/env python3
+"""
+Example usage of TinyStories SLM model
+"""
+
+import torch
+import tiktoken
+from model import GPT, GPTConfig
+
+def load_model():
+    """Load the model and tokenizer"""
+    # Load tokenizer
+    enc = tiktoken.get_encoding("gpt2")
+    
+    # Model configuration
+    config = GPTConfig(
+        vocab_size=50257,
+        block_size=128,
+        n_layer=6,
+        n_head=6,
+        n_embd=384,
+        dropout=0.0,  # Set to 0 for inference
+        bias=True
+    )
+    
+    # Load model
+    model = GPT(config)
+    model.load_state_dict(torch.load('pytorch_model.bin', map_location='cpu'))
+    model.eval()
+    
+    return model, enc
+
+def generate_story(model, enc, prompt, max_tokens=200, temperature=1.0, top_k=None):
+    """Generate a story from a prompt"""
+    context = torch.tensor(enc.encode_ordinary(prompt)).unsqueeze(0)
+    
+    with torch.no_grad():
+        generated = model.generate(
+            context, 
+            max_new_tokens=max_tokens,
+            temperature=temperature,
+            top_k=top_k
+        )
+    
+    return enc.decode(generated.squeeze().tolist())
+
+if __name__ == "__main__":
+    # Load model
+    model, enc = load_model()
+    
+    # Example prompts
+    prompts = [
+        "Once upon a time there was a pumpkin.",
+        "A little girl went to the woods",
+        "Once upon a time in India",
+        "The magic cat could",
+        "In a small village"
+    ]
+    
+    print("TinyStories SLM - Story Generation Examples")
+    print("=" * 50)
+    
+    for i, prompt in enumerate(prompts, 1):
+        print(f"\nExample {i}:")
+        print(f"Prompt: {prompt}")
+        print("-" * 30)
+        story = generate_story(model, enc, prompt, max_tokens=150, temperature=0.8)
+        print(story)
+        print("=" * 50)