HuggingFace镜像/mitra-classifier-1.1
模型介绍文件和版本分析
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Mitra 分类器

Mitra 分类器是一种表格基础模型，它在纯合成数据集上进行预训练，这些数据集是从多种随机分类器中采样得到的。

架构

Mitra 基于一个包含 7200 万参数的 12 层 Transformer，通过融入上下文学习范式进行预训练。

使用方法

要使用 Mitra 分类器，请通过运行以下命令安装 AutoGluon：

pip install uv
uv pip install autogluon.tabular[mitra]

一个展示如何使用 Mitra 分类器执行推理的极简示例：

import pandas as pd
from autogluon.tabular import TabularDataset, TabularPredictor
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_wine

# Load datasets
wine_data = load_wine()
wine_df = pd.DataFrame(wine_data.data, columns=wine_data.feature_names)
wine_df['target'] = wine_data.target

print("Dataset shapes:")
print(f"Wine: {wine_df.shape}")

# Create train/test splits (80/20)
wine_train, wine_test = train_test_split(wine_df, test_size=0.2, random_state=42, stratify=wine_df['target'])

print("Training set sizes:")
print(f"Wine: {len(wine_train)} samples")

# Convert to TabularDataset
wine_train_data = TabularDataset(wine_train)
wine_test_data = TabularDataset(wine_test)

# Create predictor with Mitra
print("Training Mitra classifier on classification dataset...")
mitra_predictor = TabularPredictor(label='target')
mitra_predictor.fit(
    wine_train_data,
    hyperparameters={
        'MITRA': {'fine_tune': False}
    },
   )

print("\nMitra training completed!")

# Make predictions
mitra_predictions = mitra_predictor.predict(wine_test_data)
print("Sample Mitra predictions:")
print(mitra_predictions.head(10))

# Show prediction probabilities for first few samples
mitra_predictions = mitra_predictor.predict_proba(wine_test_data)
print(mitra_predictions.head())

# Show model leaderboard
print("\nMitra Model Leaderboard:")
mitra_predictor.leaderboard(wine_test_data)

一个展示如何使用 mitra-classifier-1.1 进行微调的简单示例：

mitra_predictor_ft = TabularPredictor(label='target')
mitra_predictor_ft.fit(
    wine_train_data,
    hyperparameters={
        'MITRA': {'fine_tune': True, 'fine_tune_steps': 10}
    },
    time_limit=120,  # 2 minutes
   )

print("\nMitra fine-tuning completed!")

# Show model leaderboard
print("\nMitra Model Leaderboard:")
mitra_predictor_ft.leaderboard(wine_test_data)

许可协议

本项目基于 Apache-2.0 许可协议授权。

参考文献

@article{zhang2025mitra,
  title={Mitra: Mixed synthetic priors for enhancing tabular foundation models},
  author={Zhang, Xiyuan and Maddix, Danielle C and Yin, Junming and Erickson, Nick and Ansari, Abdul Fatir and Han, Boran and Zhang, Shuai and Akoglu, Leman and Faloutsos, Christos and Mahoney, Michael W and others},
  journal={arXiv preprint arXiv:2510.21204},
  year={2025}
}

Amazon 科学博客：Mitra: Mixed synthetic priors for enhancing tabular foundation models