transformers.js
web-ai
| transformers.js | web-ai | |
|---|---|---|
| 27 | 2 | |
| 7,943 | 777 | |
| - | - | |
| 9.3 | 7.2 | |
| 7 days ago | 6 months ago | |
| JavaScript | TypeScript | |
| Apache License 2.0 | MIT License |
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transformers.js
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Transformers.js: Machine Learning for the Web
We have some other WebGPU demos, including:
- WebGPU embedding benchmark: https://huggingface.co/spaces/Xenova/webgpu-embedding-benchm...
- Real-time object detection: https://huggingface.co/spaces/Xenova/webgpu-video-object-det...
- Real-time background removal: https://huggingface.co/spaces/Xenova/webgpu-video-background...
- WebGPU depth estimation: https://huggingface.co/spaces/Xenova/webgpu-depth-anything
- Image background removal: https://huggingface.co/spaces/Xenova/remove-background-webgp...
You can follow the progress for full WebGPU support in the v3 development branch (https://github.com/xenova/transformers.js/pull/545).
To answer your question, while there are certain ops missing, the main limitation at the moment is for models with decoders... which are not very fast (yet) due to inefficient buffer reuse and many redundant copies between CPU and GPU. We're working closely with the ORT team to fix these issues though!
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Deep Learning in JavaScript
BTW: you might want to add support for typed arrays.
See: https://github.com/xenova/transformers.js/blob/8804c36591d11...
This is really old, but added as part of the shape of the vector as well: https://github.com/nicolaspanel/numjs/blob/master/src/dtypes...
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Deja-Vu your AI✦ Bookmarking Tool
Made possible by Xenova and Supabase / gte-small
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Extracting YouTube video data with OpenAI and LangChain
To build the application, you’ll use the youtube-transcript package to retrieve YouTube video transcripts. You will then use LangChain and the Transformers.js package to generate free Hugging Face embeddings for the given transcript and store them in a vector store instead of relying on potentially expensive OpenAI embeddings. Lastly, you will use LangChain and an OpenAI model to retrieve information stored in the vector store.
- Transformers.js releases Zero-shot audio classification support
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How to Use AI/ML Models for Your Projects
Transformers.js: A groundbreaking library, Transformers.js brings transformer models like GPT-3, BERT, and Whisper straight to your browser. With the introduction of technologies like webGPU and LLM, Transformers.js has garnered significant attention. If you’d like to learn how to integrate a small model in the UI, check out their code and examples here.
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Show HN: Tiny LLMs – Browser-based private AI models for a wide array of tasks
The announcement seems somewhat disingenuous. The PR[1] found from their release notes[2] seems to contain only boilerplate and no real support for Mistral models or their weights.
[1]: https://github.com/xenova/transformers.js/pull/379
- Transformers.js
- Transformers.js: Run Machine Learning models directly in the browser
- What is the most cost-efficient way to have an embedding generator endpoint that is using an open-source embedding model? [Q]
web-ai
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Transformers.js
How does this compare to this project: https://github.com/visheratin/web-ai
Does it support using custom ONNX models?
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Library for running deep learning models in the browser
The library repo - https://github.com/visheratin/web-ai
What are some alternatives?
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
spark-nlp - State of the Art Natural Language Processing
web-stable-diffusion - Bringing stable diffusion models to web browsers. Everything runs inside the browser with no server support.
memory64 - Memory with 64-bit indexes
whisper.cpp - Port of OpenAI's Whisper model in C/C++
vertex-ai-samples - Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud
rust-bert - Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
openai-java - OpenAI Api Client in Java