Environment:Huggingface Alignment handbook Python Datasets
| Knowledge Sources | |
|---|---|
| Domains | NLP, Data_Engineering |
| Last Updated | 2026-02-07 00:00 GMT |
Overview
Python environment with HuggingFace Datasets >= 4.0.0 providing dataset loading, concatenation, shuffling, and train/test splitting for alignment training.
Description
The HuggingFace Datasets library provides the data loading and processing infrastructure for all alignment-handbook training workflows. The get_dataset function in src/alignment/data.py uses datasets.load_dataset to load individual datasets or create weighted mixtures via concatenate_datasets. It supports column selection, weighted subsampling, shuffling, and automatic train/test splitting.
Usage
Use this environment for any dataset loading operation in the alignment-handbook. Required by both the Get_Dataset (single dataset) and Get_Dataset_Mixture (weighted mixture) implementations.
System Requirements
| Category | Requirement | Notes |
|---|---|---|
| Python | >= 3.10.9 | Required by the alignment-handbook package |
| Network | Internet access | For downloading datasets from HuggingFace Hub |
| Disk | Variable | Datasets are cached locally; large datasets (UltraChat, UltraFeedback) require several GB |
Dependencies
Python Packages
- `datasets` >= 4.0.0
- `huggingface-hub` >= 0.33.4, < 1.0
Credentials
- HuggingFace Login: Required for accessing gated datasets.
Quick Install
# Installed as part of alignment-handbook
uv pip install .
# Or install standalone
pip install datasets>=4.0.0
Code Evidence
Datasets version requirement from `setup.py:47`:
"datasets>=4.0.0",
Datasets imports in `src/alignment/data.py:17-18`:
import datasets
from datasets import DatasetDict, concatenate_datasets
Dataset loading in `src/alignment/data.py:37`:
return datasets.load_dataset(args.dataset_name, args.dataset_config)
Dataset mixture creation in `src/alignment/data.py:61`:
combined_dataset = concatenate_datasets(datasets_list)
Common Errors
| Error Message | Cause | Solution |
|---|---|---|
| `ValueError: Either dataset_name or dataset_mixture must be provided` | No dataset specified in config | Add `dataset_name` or `dataset_mixture` to your YAML config |
| `ValueError: No datasets were loaded from the mixture configuration` | Empty dataset list in mixture config | Ensure `dataset_mixture.datasets` contains at least one entry |
| `ValueError: Column names must be consistent across all dataset configurations` | Mismatched columns in mixture datasets | Ensure all datasets in the mixture specify the same column names |
Compatibility Notes
- dataset_num_proc: Recipes set this to 12 or 48 for parallel dataset preprocessing. Adjust based on available CPU cores.
- Column format: SFT datasets require a messages column; DPO/ORPO datasets require chosen and rejected columns.