Add README with usage instructions

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3-1.7B
+tags:
+  - vibescript
+  - code-compression
+  - lora
+  - gguf
+  - qwen3
+language:
+  - en
+pipeline_tag: text-generation
+---
+
+# VibeScript - Code to DSL Converter
+
+**vibecoder-discern** converts natural language and code into VibeScript - a compact symbolic DSL for expressing programming concepts.
+
+## What is VibeScript?
+
+VibeScript compresses verbose code into symbolic notation:
+
+| Code | VibeScript |
+|------|------------|
+| `function add(a, b) { return a + b; }` | `Ω> add!(a, b)` |
+| `const users = await db.query(...)` | `δ.m.p.query()` |
+| `app.get('/api/users', ...)` | `θ.m.route(θ.e, ζ.x)` |
+| `if (error) { throw new Error(...) }` | `~system~γ#error!` |
+
+## Model Variants
+
+| Path | Format | Size | Use Case |
+|------|--------|------|----------|
+| `/lora-adapter/` | LoRA | ~13MB | Merge with your own Qwen3-1.7B |
+| `/merged-model/` | HuggingFace | ~3.4GB | Ready-to-use transformers |
+| `/gguf/` | GGUF Q4_K_M | ~1.1GB | llama.cpp / Ollama |
+
+## Quick Start
+
+### llama.cpp (GGUF)
+
+```bash
+# Download
+wget https://huggingface.co/calebboud/vibescript/resolve/main/gguf/vibecoder-discern-1.7B-Q4_K_M.gguf
+
+# Run
+llama-cli -m vibecoder-discern-1.7B-Q4_K_M.gguf \
+  -p "Convert this to vibescript: function multiply(x, y) { return x * y; }" \
+  -n 100 --temp 0.7
+```
+
+### Transformers (Merged Model)
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("calebboud/vibescript", subfolder="merged-model")
+tokenizer = AutoTokenizer.from_pretrained("calebboud/vibescript", subfolder="merged-model")
+
+prompt = "Convert this to vibescript: console.log('Hello World')"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=50)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+### LoRA Adapter (Merge Yourself)
+
+```python
+from peft import PeftModel
+from transformers import AutoModelForCausalLM
+
+base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-1.7B")
+model = PeftModel.from_pretrained(base, "calebboud/vibescript", subfolder="lora-adapter")
+merged = model.merge_and_unload()
+```
+
+## Training Details
+
+- **Base Model:** Qwen/Qwen3-1.7B
+- **Method:** LoRA (r=8, alpha=16)
+- **Target Modules:** q_proj, k_proj, v_proj, o_proj
+- **Dataset:** 885 code → vibescript examples
+- **Task:** CAUSAL_LM
+
+## VibeScript Symbols
+
+| Symbol | Meaning |
+|--------|---------|
+| `Ω>` | Function definition |
+| `Σ` | Route/scaffold |
+| `δ` | Database operations |
+| `θ` | HTTP/API |
+| `γ` | Error handling |
+| `ζ` | Structure/scaffold |
+| `α` | Analysis |
+| `ε` | Dependencies |
+
+## Coming Soon
+
+- **vibecoder-expand**: VibeScript → Code (reverse direction)
+
+## License
+
+Apache 2.0