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README.md

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+---
+license: mit
+task_categories:
+- text-classification
+tags:
+- peptide
+- mhc
+- hla
+- binding-prediction
+- immunology
+size_categories:
+- n>1M
+---
+
+# PM (Peptide-MHC) Binding Prediction Dataset
+
+## Dataset Description
+
+This dataset is part of the SPRINT benchmark framework for TCR-pMHC binding prediction. It contains peptide-MHC binding data for training and in-distribution testing of binding prediction models.
+
+### Dataset Summary
+
+The PM dataset focuses on peptide-MHC binding prediction without TCR information. It is reorganized and standardized from multiple sources to provide a clean benchmark for PM task evaluation.
+
+## Dataset Structure
+
+### Files
+
+- `train.csv`: Training data
+- `id_test.csv`: In-distribution test data
+
+### Data Format
+
+Each CSV file contains the following columns:
+
+| Column | Type | Description |
+|--------|------|-------------|
+| peptide | string | Peptide amino acid sequence |
+| HLA | string | HLA allele (standardized format: A*02:01) |
+| label | float | Binding affinity (continuous values) |
+| HLA_sequence | string | HLA pseudo-sequence |
+
+### Dataset Statistics
+
+**Training Set:**
+- Total samples: 2098450
+- Label type: Continuous (binding affinity)
+- Label range: 0.0000 - 1.0000
+- Unique HLAs: 112
+- Unique peptides: 1834505
+- Peptide length range: 8-14
+
+**Test Set (In-Distribution):**
+- Total samples: 171438
+- Label type: Continuous (binding affinity)
+- Label range: 0.0000 - 1.0000
+- Unique HLAs: 112
+- Unique peptides: 158145
+- Peptide length range: 8-14
+
+## Usage
+
+### Load with Pandas
+
+```python
+from huggingface_hub import hf_hub_download
+import pandas as pd
+
+# Download files
+train_file = hf_hub_download(
+    repo_id="YYJMAY/pm-binding",
+    filename="train.csv",
+    repo_type="dataset"
+)
+test_file = hf_hub_download(
+    repo_id="YYJMAY/pm-binding",
+    filename="id_test.csv",
+    repo_type="dataset"
+)
+
+# Load data
+train_df = pd.read_csv(train_file)
+test_df = pd.read_csv(test_file)
+```
+
+### Use with SPRINT Framework
+
+```python
+from sprint.core.dataset_manager import DatasetManager
+
+manager = DatasetManager()
+config = {
+    'hf_repo': 'YYJMAY/pm-binding',
+    'files': ['train.csv', 'id_test.csv']
+}
+
+files = manager.get_dataset('pm', config)
+```
+
+## Data Preparation
+
+This dataset was prepared with the following steps:
+
+1. **Source Integration**: Combined data from multiple PM binding datasets
+2. **HLA Standardization**: Normalized HLA allele names to A*02:01 format
+3. **Quality Control**: Removed duplicates and incomplete entries
+4. **Column Standardization**: Unified column names and formats
+5. **Validation**: Checked for data consistency and quality
+
+## Tasks
+
+This dataset is designed for:
+
+- **Peptide-MHC Binding Prediction**: Predicting binding affinity between peptides and MHC molecules
+- **In-Distribution Evaluation**: Testing model performance on similar data distribution as training
+- **Baseline Comparison**: Standardized data for reproducible benchmarking
+
+## Citation
+
+If you use this dataset, please cite:
+
+```bibtex
+@dataset{pm_dataset_2024,
+  title={PM (Peptide-MHC) Binding Prediction Dataset},
+  author={SPRINT Framework Contributors},
+  year={2024},
+  url={https://huggingface.co/datasets/YYJMAY/pm-binding}
+}
+```
+
+## License
+
+MIT License
+
+## Contact
+
+For questions or issues, please refer to the SPRINT framework repository.