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Decision brief
Pre-trained AI models for ailia SDK, covering broad applications from action recognition to audio processing.
Good fit when
- When developing apps that integrate with the ailia SDK
- For quick deployment of state-of-the-art models specific to ailia's supported categories
Avoid when
- If your project does not align with ailia SDK or its specific model categories
- When you require customization beyond what is offered by pre-trained models in this repository
Observed Jul 12, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of today
- Provenance
- Not a fork · Organization account
- As of today
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install ailia-modelsSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Collection of state-of-the-art AI models for various applications including action recognition, anomaly detection, audio processing, and more.
Capability facts
- Languages
- python
Source: github.language · Aug 22, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Tags
README
The collection of pre-trained, state-of-the-art AI models: 418 models covering object detection, speech recognition, image generation, LLMs and more — all runnable from the same simple CLI.
Tutorial · チュートリアル · Google Colaboratory · Documentation · deepwiki · Update history
Every model works the same way: no arguments needed, weights download automatically.
pip3 install ailia
git clone https://github.com/ailia-ai/ailia-models
cd ailia-models
pip3 install -r requirements.txt
cd object_detection/yolox
python3 yolox.py
Models
418 models are available. Use 🔍 Search models to find a model by name.
| Category | Model list | |
|---|---|---|
| Action recognition | va-cnn, st-gcn, mars, ax_action_recognition, driver-action-recognition-adas, action_clip | |
| Anomaly detection | mahalanobisad, spade-pytorch, padim, patchcore, glass | |
| Audio language model | qwen_audio | |
| Audio processing | Audio classification: crnn_audio_classification, audioset_tagging_cnn, transformer-cnn-emotion-recognition, microsoft clap, clap Music enhancement: hifigan, deep music enhancer Music generation: pytorch_wavenet Noise reduction: rnnoise, voicefilter, unet_source_separation, demucs, dtln, audiosep Phoneme alignment: narabas Pitch detection: crepe Speaker diarization: pyannote-audio, auto_speech, wespeaker Speech to text: deepspeech2, whisper, reazon_speech, distil-whisper, sensevoice, reazon_speech2, kotoba-whisper, lite-whisper Text to speech: pytorch-dc-tts, tacotron2, vall-e-x, Bert-VITS2, gpt-sovits, gpt-sovits-v2, cosyvoice2, gpt-sovits-v3, gpt-sovits-v2-pro, qwen3-tts **Voice |
For agents
This page has a .md twin and JSON over the API.