transformers.js
web-stable-diffusion
| transformers.js | web-stable-diffusion | |
|---|---|---|
| 27 | 21 | |
| 7,943 | 3,482 | |
| - | 1.4% | |
| 9.3 | 4.4 | |
| 7 days ago | 3 months ago | |
| JavaScript | Jupyter Notebook | |
| Apache License 2.0 | Apache License 2.0 |
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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-stable-diffusion
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GPU-Accelerated LLM on a $100 Orange Pi
Yup, here's their web stable diffusion repo: https://github.com/mlc-ai/web-stable-diffusion
The input is a model (weights + runtime lib) compiled via the mlc-llm project: https://mlc.ai/mlc-llm/docs/compilation/compile_models.html
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StableDiffusion can now run directly in the browser on WebGPU
The MLC team got that working back in March: https://github.com/mlc-ai/web-stable-diffusion
Even more impressively, they followed up with support for several Large Language Models: https://webllm.mlc.ai/
- Web StableDiffusion
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[Stable Diffusion] Diffusion stable Web: exécution de diffusion stable directement dans le navigateur sans serveur GPU
[https://github.com/mlc-ai/web-stable-diffusion
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Now that they started banning stable diffusion on google colab, what's the cheapest and the best way to deploy stable diffusion?
You can run it directly in the browser with WebGPU, https://mlc.ai/web-stable-diffusion/
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I've got Stable Diffusion integrated into my site now, fully client side with no setup or servers.
Using the amazing work of https://mlc.ai/web-stable-diffusion/ I've got the code moved into a Web Worker and running fully local client side. It does require 2GB's of model files be downloaded (automatically), and takes a few minutes for the first load, but it works and once it's going it only takes 20s to make a 512x512 image.
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Chrome Ships WebGPU
The Apache TVM machine learning compiler has a WASM and WebGPU backend, and can import from most DNN frameworks. Here's a project running Stable Diffusion with webgpu and TVM [1].
Questions exist around post-and-pre-processing code in folks' Python stacks, with e.g. NumPy and opencv. There's some NumPy to JS transpilers out there, but those aren't feature complete or fully integrated.
[1] https://github.com/mlc-ai/web-stable-diffusion
- Bringing stable diffusion models to web browsers
- mlc-ai/web-stable-diffusion: Bringing stable diffusion models to web browsers. Everything runs inside the browser with no server support.
- Web Stable Diffusion: Running Diffusion Models with WebGPU
What are some alternatives?
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
stable-diffusion-webui-amdgpu - Stable Diffusion web UI
web-ai - Run modern deep learning models in the browser.
rust-bert - Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
spark-nlp - State of the Art Natural Language Processing
SHA256-WebGPU - Implementation of sha256 in WGSL
memory64 - Memory with 64-bit indexes
wgpu-py - The next generation GPU API for Python
vertex-ai-samples - Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud
openai-java - OpenAI Api Client in Java
js-promise-integration - JavaScript Promise Integration