Update ML Intern artifact metadata

README.md

@@ -1,3 +1,7 @@
+---
+tags:
+- ml-intern
+---
 # 风控序列模型调研报告 & 代码模板
 
 ## 📋 文件清单
@@ -46,3 +50,23 @@ pip install torch pytorch-lifestream scikit-learn lightgbm pandas numpy scipy
 1. **App序列**：用 GRU + CoLES 对比学习（无标签预训练→LightGBM），不要默认 Transformer
 2. **征信数据**：先 LightGBM baseline，再 TabM+PLE 补充，0.5:0.5 集成
 3. **两个模型分开建**，最后 Late Fusion（向量拼接→LightGBM stacking）
+
+<!-- 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 = "yonghao/risk-control-sequence-models"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+```
+
+For non-causal architectures, replace `AutoModelForCausalLM` with the appropriate `AutoModel` class.