Update top-level README

README.md

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+---
+library_name: peft
+license: apache-2.0
+tags:
+- lora
+- monkey-research
+- arith_op
+---
+
+# monkey-cpt-arith_op
+
+Continued-pretraining (CPT) LoRA adapters, one per synthetic-document bundle condition.
+
+From the project *Tell or Show: How Training-Data Format Shapes Implicit
+vs. Explicit Rule Knowledge*.
+
+## Layout
+
+Adapters are organized as `<base-model>/<bundle-condition>/`:
+
+```
+.
+└── qwen3-4b-instruct-2507/       # base = Qwen/Qwen3-4B-Instruct-2507
+    ├── fewshot/
+    ├── explicit/
+    └── explicit_fewshot/
+```
+
+Each leaf subdir is a self-contained PEFT-loadable adapter:
+- `adapter_config.json`
+- `adapter_model.safetensors`
+- `README.md` (per-variant details)
+- `trainer_state.json` (training-time metrics)
+
+Future base models (Qwen3-7B etc.) will appear as sibling base-model dirs.
+
+## Loading
+
+```python
+from peft import PeftModel
+from transformers import AutoModelForCausalLM
+
+base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B-Instruct-2507", torch_dtype="bfloat16")
+model = PeftModel.from_pretrained(base, "ada-flo/monkey-cpt-arith_op", subfolder="qwen3-4b-instruct-2507/fewshot")
+```