Update ML Intern artifact metadata

README.md

@@ -2,12 +2,13 @@
 license: mit
 library_name: xgboost
 tags:
-  - agent-cost-optimizer
-  - model-router
-  - cost-aware-inference
-  - cascade-routing
-  - execution-feedback
-  - swebench
+- agent-cost-optimizer
+- model-router
+- cost-aware-inference
+- cascade-routing
+- execution-feedback
+- swebench
+- ml-intern
 ---
 
 # ACO v10: Agent Cost Optimizer
@@ -88,3 +89,23 @@ print(f"Step type: {d.step_type.value}, Tier: {d.adjusted_tier}, Cost: ${d.cost_
 ## License
 
 MIT
+
+<!-- ml-intern-provenance -->
+## Generated by ML Intern
+
+This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub.
+
+- Try ML Intern: https://smolagents-ml-intern.hf.space
+- Source code: https://github.com/huggingface/ml-intern
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = 'narcolepticchicken/agent-cost-optimizer'
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+```
+
+For non-causal architectures, replace `AutoModelForCausalLM` with the appropriate `AutoModel` class.