jonhue/activeft
PyTorch library for Active Fine-Tuning
This library helps machine learning researchers and practitioners automatically select the most informative data points for fine-tuning large neural networks. It takes your existing dataset embeddings and query embeddings, then outputs a curated subset of data that will most effectively improve your model's performance with less effort. This is ideal for those working on optimizing large language models or other deep learning applications.
No commits in the last 6 months. Available on PyPI.
Use this if you need to efficiently improve the performance of large neural networks by strategically choosing which data to use for fine-tuning, rather than training on your entire dataset.
Not ideal if you are looking for a general-purpose machine learning library for model training from scratch or if you don't work with large neural networks and fine-tuning.
Stars
97
Forks
9
Language
Python
License
MIT
Category
Last pushed
Sep 27, 2025
Commits (30d)
0
Dependencies
1
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/jonhue/activeft"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
ntucllab/libact
Pool-based active learning in Python
scikit-activeml/scikit-activeml
scikit-activeml: A Comprehensive and User-friendly Active Learning Library
python-adaptive/adaptive
:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
NUAA-AL/ALiPy
ALiPy: Active Learning in Python is an active learning python toolbox, which allows users to...
ai4co/awesome-fm4co
Recent research papers about Foundation Models for Combinatorial Optimization