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27 readable replies · Supporting reply 1 · Supporting reply 2 · Supporting reply 3 · Supporting reply 4huggingface
transformers.js
JavaScript2023–2026
huggingface / transformers.js
transformers.js
State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!
17Distinct people
25Mentions
0Explicit recommenders
16.4KGitHub stars
What to know before exploring
What it is
State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!
GitHub
Where it is used
No documented product use was verified in the last source check.
What people are saying
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Also in these discussions
- electric-sql/pglite · linked in 3 of the same discussions
- supabase-community/pg-gateway · linked in 3 of the same discussions
Mentioned in the same Hacker News threads. That is not proof they are substitutes.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.
Mentions over time
HN mentions by year25 dated mentions
Observed mentions: 2023-03-17 01:02:42 UTC to 2026-10-26 14:20:49 UTC.
* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 10 | 4 | 6 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 9 | 3 | 6 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 3 | 0 | 3 |
| 2026 (partial) | 2026-01-01 00:00:00 UTC | 2027-01-01 00:00:00 UTC | 3 | 2 | 1 |
What Hacker News says
25 sourcesSRsroussey·Oct 26, 2026
Constrained decoding came to JS land transformers last month for in browser structured output as well, also used for tool calling.
https://github.com/huggingface/transformers.js/blob/main/pac...
In Fixing Tool-Call Accuracy in vLLMRelease 4.0.0 · HuggingFace/Transformers.js
2 points · Open discussionHuggingFace has just released Transformer.js v4 with WebGPU support
2 points · Open discussionVery cool!
For some awesome examples of running different types of models in webgpu check out the examples folder here. https://github.com/huggingface/transformers.js
In Show HN: WebGPU enables local LLM in the browser – demo site with AI chatI built a Chrome extension with one feature that transcribes audio to text in the browser using huggingface/transformers.js running the OpenAI Whisper model with WebGPU. It works perfect! Here is a list of examples of all the things you can do in the browser with webgpu for free. [0]
The last thing in the world I want to do is listen or watch presidential social media posts, but, on the other hand, sometimes enormously stupid things are said which move the SP500 up or down $60 in a session. So this feature queries for new posts every minute, does ORC image to text and transcribe video audio to text locally, sends the post with text for analysis, all in the background inside a Chrome extension before notify me of anything economically significant.
[0] https://github.com/huggingface/transformers.js/tree/main/exa...
[1] https://github.com/ad
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Another very cool attribute of embeddings and embedding search is that they are resource cheap enough that you can perform them client side.
ONNX models can be loaded and executed with transformer.js https://github.com/huggingface/transformers.js/
You can even build and statically host indices like hnsw for embeddings.
I put together a little open source demo for this here https://jasonjmcghee.github.io/portable-hnsw/ (it's a prototype / hacked together approximation of hnsw, but you could implement the real thing)
Long story short, represent indices as queryable parquet files and use duckdb to query them.
Depending on how you host, it's either free or nearly free. I used Github Pages so it's free. R2 with cloudflare would only cost the size what you store (very cheap- no egress fees).
In Embeddings are underrated (2024)Transformers.js 3.0 Released with WebGPU Support
33 points · Open discussionEverything is open source with the exception of the LLM at the moment, which we'll get to. Here are all the tools:
* postgres-new (https://github.com/supabase-community/postgres-new): The frontend. Apache 2.0
* PGlite (https://github.com/electric-sql/pglite): A WASM build of Postgres. Apache 2.0
* pg-gateway (https://github.com/supabase-community/pg-gateway): Postgres wire protocol for the server-side. MIT
* transformers.js (https://github.com/xenova/transformers.js): Run Transformers directly in your browser
In Postgres.new: In-browser Postgres with an AI interfacehey HN, supabase ceo here. Full details here: https://supabase.com/blog/postgres-new
This is a new service that we're experimenting with that uses PGLite[0], a WASM build of Postgres that runs in the browser. You might remember an earlier WASM build[1] that was around ~30MB. The Electric team [2] have gone one step further and created a complete build of Postgres that’s under 3MB.
Their implementation is technically interesting. Postgres is normally multi-process - each client connection is handed to a child process by the postmaster process. In WASM there’s limited/no support for process forking and threads. Fortunately, Postgres has a relatively unknown built-in “single user mode” [3] primarily designed for bootstrapping a new database and disaster recovery. Single-user mode only supports a minimal cancel REPL, so PGlite adds wire-proto
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col support which enables parametrised queries etc.
We have created https://postgres.new as an experiment. You can think of it like a love-child between Postgres and ChatGPT: in-browser Postgres sandbox with AI assistance. You can spin up as many new Postgres databases as you want because they all live inside your browser. We pair PGlite with an LLM (currently GPT-4o) and give it full reign over the database with unrestricted permissions. This is an important detail - giving an LLM full autonomy means that it can run multiple operations back-to-back: any SQL errors from Postgres are fed back to the language model so that it can have a few more attempts to solve the problem. Since it’s in-browser it’s low risk.
Some other features include:
- CSV upload: you can upload a CSV and it will automatically create a Postgres table which you can query with natural language.
- Charts: you can ask the LLM to create a chart with the data and change the colors of the charts.
- RAG / pgvector: PGLite supports pgvector, so you can ask the LLM to create embeddings for RAG. The site uses transformers.js [4] to create embeddings inside the browser.
We’re working on an update to deploy your databases and serve them from S3 using pg-gateway [5]. We expect to have a read-only deployments ready by the end of the week. You can access them using any postgres-compatible tool (eg: psql).
Everything is open source. A huge shout-out to the Electric team who have been a pleasure to build with.
[0] PGLite: https://github.com/electric-sql/pglite
[1] Postgres-wasm: https://supabase.com/blog/postgres-wasm
[2] Electric: https://electric-sql.com/
[3] Single user mode: https://www.postgresql.org/docs/current/app-postgres.html#AP...
[4] transformers.js: https://github.com/xenova/transformers.js
[5] pg-gateway: https://github.com/supabase-community/pg-gateway
Postgres.new: In-browser Postgres with an AI interface
hey HN, supabase ceo here
This is a new service that we're experimenting with that uses PGLite[0], a WASM build of Postgres that runs in the browser. You might remember an earlier WASM build[1] that was around ~30MB. The Electric team [2] have gone one step further and created a complete build of Postgres that’s under 3MB.
Their implementation is technically interesting. Postgres is normally multi-process - each client connection is handed to a child process by the postmaster process. In WASM there’s limited/no support for process forking and threads. Fortunately, Postgres has a relatively unknown built-in “single user mode” [3] primarily designed for bootstrapping a new database and disaster recovery. Single-user mode only supports a minimal cancel REPL, so PGlite adds wire-protocol support which enables parametrised queries etc.
We have
Read the rest
created https://postgres.new as an experiment. You can think of it like a love-child between Postgres and ChatGPT: in-browser Postgres sandbox with AI assistance. You can spin up as many new Postgres databases as you want because they all live inside your browser. We pair PGlite with an LLM (currently GPT-4o) and give it full reign over the database with unrestricted permissions. This is an important detail - giving an LLM full autonomy means that it can run multiple operations back-to-back: any SQL errors from Postgres are fed back to the language model so that it can have a few more attempts to solve the problem. Since it’s in-browser it’s low risk.
Some other features include:
- CSV upload: you can upload a CSV and it will automatically create a Postgres table which you can query with natural language.
- Charts: you can ask the LLM to create a chart with the data and change the colors of the charts.
- RAG / pgvector: PGLite supports pgvector, so you can ask the LLM to create embeddings for RAG. The site uses transformers.js [4] to create embeddings inside the browser.
We’re working on an update to deploy your databases and serve them from S3 using pg-gateway [5]. We expect to have a read-only deployments ready by the end of the week. You can access them using any postgres-compatible tool (eg: psql).
Everything is open source. A huge shout-out to the Electric team who have been a pleasure to build with.
[0] PGLite: https://github.com/electric-sql/pglite
[1] Postgres-wasm: https://supabase.com/blog/postgres-wasm
[2] Electric: https://electric-sql.com/
[3] Single user mode: https://www.postgresql.org/docs/current/app-postgres.html#AP...
[4] transformers.js: https://github.com/xenova/transformers.js
[5] pg-gateway: https://github.com/supabase-community/pg-gateway
This looks really promising and thanks for sharing! I've actually been looking into this exact type of functionality lately, for anyone else I'm just going to drop some other projects in this area (also if anyone, including OP, want's to chime in on how they compare- i know there's all sorts of trade-offs ie. the similarity algo chosen, one of these relies on wasm, etc):
https://github.com/tantaraio/voy
https://github.com/nitaiaharoni1/vector-storage
https://github.com/danielivanovz/indexed-vector-store
https://github.com/yusufhilmi/client-vector-search
Another area I've looked into briefly is also trying to generate vector embeddings fully in-browser. I know there will likely be tradeoffs with dimensionality / overall accuracy/performance but having a semi-decent way to do this in-browser would be awesome.
This project only runs in node
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(but there's an issue that talks about how it might be modified to run in-browser):
https://github.com/Anush008/fastembed-js
Looks like transformers.js supports embeddings in-browser:
https://github.com/xenova/transformers.js/releases/tag/2.1.0
https://github.com/pinecone-io/semantic-search-example/blob/...
Also it appears the client-vector-search supports both embeddings & vector indexing
https://github.com/yusufhilmi/client-vector-search
Hope this helps others looking into this stuff!
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 c
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opies between CPU and GPU. We're working closely with the ORT team to fix these issues though!
This library is so cool. It makes spinning up a quick demo incredibly easy - I've used it in Observable notebooks a few times:
- CLIP in a browser: https://observablehq.com/@simonw/openai-clip-in-a-browser
- Image object detection with detra-resnet-50: https://observablehq.com/@simonw/detect-objects-in-images
The size of the models feels limiting at first, but for quite a few applications telling a user with a good laptop and connection that they have to wait 30s for it to load isn't unthinkable.
The latest releases adds binary embedding quantization support which I'm really looking forward to trying out: https://github.com/xenova/transformers.js/releases/tag/2.17....
In Transformers.js – Run Transformers directly in the browserTransformers.js – Run Transformers directly in the browser
239 points · Open discussionBTW: 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...
In Deep Learning in JavaScriptShowing the 15 most recent of 25 sources. Enable JavaScript to search and browse every indexed mention.