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MachineLearningML: Continued Pretraining Language Models on Millions of Synthetic Tabular Prediction Tasks Scales In-Context ML |
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license: apache-2.0 |
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base_model: |
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- Qwen/Qwen2.5-7B-Instruct |
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--- |
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# MachineLearningLM |
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## model summary |
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Can LLMs learn from 1,000 in-context examples? |
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Introducing **MachineLearningLM** 🧪📊 — a model continuously pretrained on millions of synthetic tabular ML tasks, enabling robust many-shot in-context learning. |
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📈 **Scales from 8 to 1,024 examples** |
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📈 **~15% improvement** on unseen tabular tasks compared to o3-mini / GPT-5-mini / Qwen-2.5-7B |
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🌲 **Random-Forest–level robustness** |
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🧠 **MMLU score: 75.4%** |
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📄 Read the paper: https://huggingface.co/papers/2509.06806 |
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GitHub: https://github.com/HaoAreYuDong/MachineLearningLM |
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## evaluation and validation |
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We have developed an automated evaluation framework — simply configure the parameters to easily perform validation and evaluation. |
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**The code is now open-sourced at our GitHub.** |
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**Quick Start** |
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```bash |
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pip install -r requirements.txt |
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python ./src/evaluation/model_pred/dl_model_pred.py \ |
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--input_dir ./demo_input.jsonl \ |
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--output_dir ./demo_output.jsonl \ |
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--model_name MachineLearningLM/MachineLearningLM-7B-v1 |
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``` |
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**pipeline** |
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```bash |
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# modify the evaluate_parameters.sh file |
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source evaluate_parameters.sh |
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# Option 1 End-to-End Pipeline |
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./scripts/evaluate_pipeline.sh |
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# Option 2 Parallel Processing |
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./scripts/multi_process/data_prep.sh |
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./scripts/multi_process/prompt_gen.sh # For deep learning only |
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./scripts/multi_process/model_pred.sh |
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./scripts/multi_process/evaluation.sh |
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./scripts/multi_process/report.sh |
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# Option3 Sequential Processing |
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./scripts/single_process/data_prep.sh |
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./scripts/single_process/prompt_gen.sh # For deep learning only |
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./scripts/single_process/model_pred.sh |
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./scripts/single_process/evaluation.sh |
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./scripts/single_process/report.sh |
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``` |
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**Quants** |
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https://huggingface.co/mradermacher/MachineLearningLM-7B-v1-GGUF |
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For more usage details, please visit our GitHub. |
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