https://github.com/lostbeard/spawndev.blazorjs.transformersjs
Use Transformers.js from Blazor WebAssembly to run pretrained models with the ONNX Runtime in the browser.
https://github.com/lostbeard/spawndev.blazorjs.transformersjs
blazor blazor-webassembly browser deep-learning depth-estimation huggingface huggingface-transformers javascript machine-learning neural-networks onnx pretrained-models tensorflow text-to-speech transformers
Last synced: 3 months ago
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Use Transformers.js from Blazor WebAssembly to run pretrained models with the ONNX Runtime in the browser.
- Host: GitHub
- URL: https://github.com/lostbeard/spawndev.blazorjs.transformersjs
- Owner: LostBeard
- License: mit
- Created: 2025-01-04T23:26:46.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-07T17:06:27.000Z (over 1 year ago)
- Last Synced: 2025-02-17T03:33:36.080Z (over 1 year ago)
- Topics: blazor, blazor-webassembly, browser, deep-learning, depth-estimation, huggingface, huggingface-transformers, javascript, machine-learning, neural-networks, onnx, pretrained-models, tensorflow, text-to-speech, transformers
- Language: C#
- Homepage: https://lostbeard.github.io/SpawnDev.BlazorJS.TransformersJS/
- Size: 46 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# SpawnDev.BlazorJS.TransformersJS
[](https://www.nuget.org/packages/SpawnDev.BlazorJS.TransformersJS)
## State-of-the-art Machine Learning for the Web in Blazor WebAssembly
`SpawnDev.BlazorJS.TrasnformersJS` brings the awesome [Transformers.js](https://github.com/huggingface/transformers.js/) library from [Hugging Face]() to Blazor WebAssembly.
Transformers.js is designed to be functionally equivalent to Hugging Face’s transformers python library, meaning you can run the same pretrained models using a very similar API. These models support common tasks in different modalities, such as:
- 📝 Natural Language Processing: text classification, named entity recognition, question answering, language modeling, summarization, translation, multiple choice, and text generation.
- 🖼️ Computer Vision: image classification, object detection, segmentation, and depth estimation.
- 🗣️ Audio: automatic speech recognition, audio classification, and text-to-speech.
- 🐙 Multimodal: embeddings, zero-shot audio classification, zero-shot image classification, and zero-shot object detection.
Transformers.js uses ONNX Runtime to run models in the browser. The best part about it, is that you can easily convert your pretrained PyTorch, TensorFlow, or JAX models to ONNX using 🤗 Optimum.
### Demo
The current demo app uses Transformers.js, Blazor, and WebGL.
**NOTE: The models used can be large. A fast connection is recommended.**
- [Live Demo](https://lostbeard.github.io/SpawnDev.BlazorJS.TransformersJS)
- [2D to 2D+Z](https://lostbeard.github.io/SpawnDev.BlazorJS.TransformersJS)
- [2D to Anaglyph](https://lostbeard.github.io/SpawnDev.BlazorJS.TransformersJS/AnaglyphImageDemo)
- [Image Enhancement](https://lostbeard.github.io/SpawnDev.BlazorJS.TransformersJS/ImageToImage)
- [Text To Speech](https://lostbeard.github.io/SpawnDev.BlazorJS.TransformersJS/TextToSpeechClient)
- [Keypoint Detection](https://lostbeard.github.io/SpawnDev.BlazorJS.TransformersJS/KeypointDetectionDemo)
- [Realtime 2D to 2DZ](https://lostbeard.github.io/SpawnDev.BlazorJS.TransformersJS/RealTime2DZ)
- [Webcam 2D to 3D](https://lostbeard.github.io/SpawnDev.BlazorJS.TransformersJS/RealTime2Dto3D)
- [Video 2D to 3D](https://lostbeard.github.io/SpawnDev.BlazorJS.TransformersJS/RealTimeVideo2Dto3D)
- [Speech Recognition](https://lostbeard.github.io/SpawnDev.BlazorJS.TransformersJS/SpeechRecognition)
#### WIP
If you are interested in this project, please start an issue to suggest features or areas of interest.