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README.md

@@ -83,56 +83,7 @@ cd monday_morning_moral
 uv sync
 ```
 
-### Loading and Generating
-
-```python
-import torch
-import tiktoken
-from models.gpt2 import GPT2
-from generate import generate, text_to_token_ids, token_ids_to_text
-from huggingface_hub import hf_hub_download
-
-# Download weights from Hugging Face
-model_path = hf_hub_download(
-    repo_id="0rn0/gpt2-30m-tinystories",
-    filename="model.safetensors"
-)
-
-# Create model with correct config
-model = GPT2(
-    dropout_rate=0.1,
-    vocab_size=50257,
-    context_length=512,
-    embedding_dim=384,
-    num_layers=6,
-    num_heads=6
-)
-
-# Load weights
-checkpoint = torch.load(model_path, map_location="cpu")
-if isinstance(checkpoint, dict) and "model_state_dict" in checkpoint:
-    model.load_state_dict(checkpoint["model_state_dict"])
-else:
-    model.load_state_dict(checkpoint)
-model.eval()
-
-# Setup tokenizer
-tokenizer = tiktoken.get_encoding("gpt2")
-
-# Generate text
-prompt = "Once upon a time"
-input_ids = text_to_token_ids(prompt, tokenizer)
-output_ids = generate(
-    model=model,
-    idx=input_ids,
-    max_new_tokens=200,
-    context_size=512,
-    temperature=0.8,
-    top_k=40,
-    eos_id=50256,
-)
-print(token_ids_to_text(output_ids, tokenizer))
-```
+See the [GitHub repository](https://github.com/aryandeore/monday_morning_moral) for usage examples and the full API reference.
 
 ## Limitations