| | --- |
| | license: mit |
| | base_model: Xenova/clap-htsat-unfused |
| | tags: |
| | - audio-classification |
| | - transformers.js |
| | - clap |
| | - audio-tagging |
| | library_name: transformers.js |
| | --- |
| | |
| | # clip-tagger Model |
| |
|
| | This is a personalized audio tagging model based on CLAP (Contrastive Language-Audio Pre-training). It extends the base Xenova/clap-htsat-unfused model with user feedback and custom tags. |
| |
|
| | ## Model Description |
| |
|
| | - **Base Model**: [Xenova/clap-htsat-unfused](https://huggingface.co/Xenova/clap-htsat-unfused) |
| | - **Framework**: Transformers.js compatible |
| | - **Training**: User feedback and custom tag integration |
| | - **Use Case**: Personalized audio content tagging |
| |
|
| | ## Usage |
| |
|
| | ```javascript |
| | import { CLAPProcessor } from './clapProcessor.js'; |
| | import { LocalClassifier } from './localClassifier.js'; |
| | |
| | // Load the model |
| | const processor = new CLAPProcessor(); |
| | const classifier = new LocalClassifier(); |
| | classifier.loadModel(); // Loads from localStorage or model files |
| | |
| | // Process audio |
| | const tags = await processor.processAudio(audioBuffer); |
| | const personalizedTags = classifier.predictAll(features, candidateTags); |
| | ``` |
| |
|
| | ## Files |
| |
|
| | - `localClassifier.js` - Local classifier implementation |
| | - `clapProcessor.js` - CLAP model wrapper |
| | - `userFeedbackStore.js` - User feedback storage system |
| | - `model-config.json` - Model configuration |
| | - `example-usage.html` - Usage example |
| |
|
| | ## Links |
| |
|
| | - **🚀 Live Demo**: [clip-tagger Space](https://huggingface.co/spaces/sohei1l/clip-tagger) |
| | - **📦 Model Repository**: [sohei1l/clip-tagger](https://huggingface.co/sohei1l/clip-tagger) |
| | - **💻 Source Code**: [GitHub Repository](https://github.com/sohei1l/clip-tagger) |
| |
|
| | ## Training Data |
| |
|
| | This model learns from user corrections and custom tags. The base CLAP model provides initial audio understanding, while the local classifier adapts to user preferences. |
| |
|
