GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
LibFewShot is a focused library designed specifically for few-shot learning tasks, emphasizing both fine-tuning and meta-learning techniques. It is particularly optimized for use cases involving image classification.
Good fit when
- When your project involves few-shot learning scenarios where adapting models with limited labeled data for image classification tasks is critical.
- If you are looking to integrate both fine-tuning and meta-learning methodologies within the same tool without the need for complex setup processes.
- Pricing:
- freemium - LibFewShot is open-source under the MIT license, making it freely available and modifiable. However, advanced features or support might require contributions or additional resources.
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Slowing (327d since push)
- As of Sep 19, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 19, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install LibFewShotSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
[TPAMI 2023] LibFewShot offers tools and methods focused on few-shot learning techniques including fine-tuning and meta-learning, primarily targeting image classification tasks.
Capability facts
- Languages
- python
Source: github.language · Sep 19, 2026
Categories
Tags
README
Quick Installation Please refer to install.md(安装) for installation. Complete tutorials can be found at document(中文文档). License This project is licensed under the MIT License. See LICENSE for more details.
For agents
This page has a .md twin and JSON over the API.