# Web Adaptation

Qwen3-1.7B is a 1.7B-parameter open-source large language model released by Alibaba Cloud, based on the Transformer architecture, supporting various natural language processing tasks.

An ONNX-optimized Whisper large speech recognition model designed for web deployment

TimeSformer is a video understanding model based on the Transformer architecture, specifically designed for video classification tasks.

Depth-Anything-V2-Base is an ONNX-format depth estimation model adapted for Transformers.js, designed for image depth estimation on the web.

Whisper is a general-purpose speech recognition model trained by OpenAI. This model is based on large-scale weakly supervised training and supports speech transcription in multiple languages.

MusicGen Small is a Transformer-based music generation model capable of producing high-quality music clips from text descriptions.

Object detection model based on YOLOv9, adapted for Transformers.js, capable of running in a browser

ONNX version of depth estimation model based on Transformers.js, suitable for web applications

A voice command recognition model based on the HuBERT architecture, optimized for keyword spotting tasks

Hybrid depth estimation model developed by Intel, combining the advantages of convolutional neural networks and Transformer architecture

Nougat is a vision-based academic document understanding model capable of converting scientific PDF images into Markdown-formatted text.

TrOCR is a Transformer-based OCR model specifically designed for recognizing printed text.

TrOCR-small-printed is a compact optical character recognition (OCR) model specifically designed for printed text recognition.

DistilBART-CNN-12-6 is a distilled version of the BART model, optimized for text summarization tasks, with a smaller size while maintaining high performance.

YOLOS is an object detection model based on the Transformer architecture, designed for efficient visual task processing.

YOLOS-small is a small object detection model based on the Transformer architecture, designed for efficient visual tasks.

E5-small-v2 is an efficient text embedding model suitable for various natural language processing tasks.

MMS-LID-4017 is a speech recognition model supporting 4017 languages, developed by Facebook, focusing on language identification tasks.

MMS-LID-126 is a multilingual speech recognition model released by Facebook, supporting recognition of 126 languages.

A voice command recognition model based on AST architecture, optimized for web deployment in ONNX format

Audio Spectrogram Transformer (AST) model fine-tuned on the AudioSet dataset for audio classification tasks

Whisper Medium is a medium-scale speech recognition model developed by OpenAI, supporting automatic speech recognition (ASR) tasks in multiple languages.

End-to-end object detection model based on Transformer architecture with ResNet-101 feature extractor

A large-scale text summarization model based on the BART architecture, optimized for the CNN/DailyMail dataset