Add model card (#3)

- Add model card (8e02dc4fbbc0905c5ffba19ab322606634087628)

README.md

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+# SuperSmallJokeClaude
+
+A 1.64M-parameter tiny transformer trained from scratch on Fable 5 Claude Code assistant traces.
+
+## Specs
+- **Params:** 1,644,032 (1.64M)
+- **Architecture:** 4-layer transformer, d_model=128, 4 heads, d_ff=256, tied embeddings
+- **Vocab:** BPE-8192 (from Claude Code tokenizer)
+- **Context:** 512 tokens
+- **Training data:** 24,249 tokens (Fable 5 Claude Code assistant traces)
+- **Training:** 2000 steps, batch 8, seq 256, AdamW lr=3e-4 cosine schedule
+- **Final loss:** 2.90
+- **Training time:** 7 seconds on RTX 5090
+
+## What it does
+
+It's a joke — a tiny model trained on tiny data. It will produce degenerate output (repeated tokens, gibberish). It exists to demonstrate that you can train a working transformer in 7 seconds on a single GPU.
+
+## Files
+- `final.pt` — full checkpoint (model state dict + config + training metadata)
+- `tokenizer.json` — BPE-8192 tokenizer (Claude Code)
+
+## Load it
+
+```python
+import torch
+from tokenizers import Tokenizer
+
+ckpt = torch.load('final.pt', map_location='cpu')
+config = ckpt['config']
+
+# Build model (see train_jokeclaude_v5.py for the class definition)
+model = Transformer(**config)
+model.load_state_dict(ckpt['model_state_dict'])
+model.eval()
+
+tokenizer = Tokenizer.from_file('tokenizer.json')
+```
+
+## Disclaimer
+This is an experimental/fun artifact. The model is not useful for any real task. It exists because someone asked for a "super small joke claude" and we said why not.