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README.md

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+---
+language: en
+tags:
+  - gpt
+  - weather
+  - character-level
+  - pytorch
+  - nano
+license: mit
+---
+
+# nanoWeatherGPT
+
+A character-level GPT (~813K parameters) trained from scratch on synthetic weather forecast text.
+
+## Download & Use
+
+```python
+from huggingface_hub import snapshot_download
+import torch, pickle, sys
+
+# Download all files
+path = snapshot_download("agoel7029/nano-weather-gpt-model")
+sys.path.insert(0, path)
+
+from model import GPT
+
+ckpt = torch.load(f"{path}/model.pt", map_location="cpu", weights_only=False)
+meta = pickle.load(open(f"{path}/meta.pkl", "rb"))
+stoi, itos = meta["stoi"], meta["itos"]
+
+model = GPT(ckpt["config"])
+model.load_state_dict(ckpt["model_state_dict"])
+model.eval()
+
+prompt = "Today the weather is"
+ctx = torch.tensor([[stoi[c] for c in prompt]], dtype=torch.long)
+with torch.no_grad():
+    out = model.generate(ctx, max_new_tokens=200)
+print("".join(itos[i] for i in out[0].tolist()))
+```
+
+## Fine-tune on your own data
+
+Edit `train.py` — replace `generate_weather_corpus()` with your own text, then run:
+
+```bash
+python train.py
+```
+
+## Model details
+
+| Property | Value |
+|---|---|
+| Architecture | Character-level GPT (Transformer) |
+| Parameters | ~813K |
+| Layers | 4 |
+| Attention heads | 4 |
+| Embedding dim | 128 |
+| Context length | 128 characters |
+| Trained on | Synthetic Swiss city weather reports |