README.md

---
MachineLearningML: Continued Pretraining Language Models on Millions of Synthetic Tabular Prediction Tasks Scales In-Context ML
license: apache-2.0
base_model:
- Qwen/Qwen2.5-7B-Instruct
---

# MachineLearningLM

## model summary

Can LLMs learn from 1,000 in-context examples?

Introducing **MachineLearningLM** 🧪📊 — a model continuously pretrained on millions of synthetic tabular ML tasks, enabling robust many-shot in-context learning.

📈 **Scales from 8 to 1,024 examples**
📈 ​**​~15% improvement​**​ on unseen tabular tasks compared to o3-mini / GPT-5-mini / Qwen-2.5-7B
🌲 ​**​Random-Forest–level robustness​**​
🧠 ​**​MMLU score: 75.4%​**​

📄 Read the paper:  https://arxiv.org/abs/2509.06806

   GitHub: https://github.com/HaoAreYuDong/MachineLearningLM

## evaluation and validation

We have developed an automated evaluation framework — simply configure the parameters to easily perform validation and evaluation. The code is now open-sourced at our GitHub.

### **Quick Start**

```bash
pip install -r requirement.txt
python ./src/evaluation/model_pred/dl_model_pred.py \
  --input_dir ./demo_input.jsonl \
  --output_dir ./demo_output.jsonl \
  --model_name hf_repo/model_name
```

For more usage details, please visit our GitHub.