ALToolbox
github.com
Spec sheet
- Purpose
- ALToolbox is a framework for active-learning annotation in natural language processing.Read 14 Nov 2026 · github.com
- License
- The project is licensed under the MIT License.Read 14 Nov 2026 · github.com
- Annotation interface
- It provides a serverless GUI annotation tool integrated into Jupyter.Read 14 Nov 2026 · github.com
- Data reusability
- It includes a PLASM postprocessing pipeline for annotated-data reusability.Read 14 Nov 2026 · github.com
- Datasets
- Custom datasets can be loaded from Hugging Face datasets or repository data files.Read 14 Nov 2026 · github.com
- Installation
- The README instructs installation with pip install acleto.Read 14 Nov 2026 · github.com
- Jupyter setup
- The annotation widget requires additional installation steps for Jupyter Notebook or JupyterLab.Read 14 Nov 2026 · github.com
- Model compatibility
- The repository supports Hugging Face Transformers models for sequence and token classification.Read 14 Nov 2026 · github.com
- Model distillation
- It includes acquisition-model distillation and domain adaptation tools.Read 14 Nov 2026 · github.com
- Query strategies
- It includes strategies such as ALPS, BADGE, BAIT, BALD, BatchBALD, and Entropy.Read 14 Nov 2026 · github.com
- Research audience
- The publication describes the framework as intended to support data scientists and researchers.Read 14 Nov 2026 · github.com
- Supported tasks
- It supports text classification and sequence tagging tasks.Read 14 Nov 2026 · github.com
- Testing
- Tests default to CUDA when available and otherwise use CPU; CPU is recommended for robust results.Read 14 Nov 2026 · github.com
Where Specifiction places it
- Active Learning Tools#8 of 167.1
