I built a machine learning pipeline for email triage. Includes a hand-labeled golden set, training the model in the browser, and evals. Plus options for local vs cloud embeddings.
Sakana AI on Twitter / X
We’re excited to introduce Doc-to-LoRA and Text-to-LoRA, two related research exploring how to make LLM customization faster and more accessible.https://t.co/wGKDNhBcJXBy training a Hypernetwork to generate LoRA adapters on the fly, these methods allow models to instantly… pic.twitter.com/gId3J6hgEr— Sakana AI (@SakanaAILabs) February 27, 2026
ml5 - A friendly machine learning library for the web.
ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies.
Gökdeniz Gülmez on Twitter / X
🚀 introducing mlx-embeddings-lora v1.0.5!„pip install -U mlx-embeddings-lora“Train your own text embedding models locally on Apple Silicon 🍏 using contrastive learning + LoRA fine-tuning — no GPUs, no cloud, just pure MLX speed.💡 Built on mlx-embeddings🧠 Supports LoRA…— Gökdeniz Gülmez (@ActuallyIsaak) November 13, 2025
Sakana AI on Twitter / X
We’re excited to introduce Text-to-LoRA: a Hypernetwork that generates task-specific LLM adapters (LoRAs) based on a text description of the task. Catch our presentation at #ICML2025!Paper: https://t.co/2FRiVF1UXJCode: https://t.co/rx4G7dq1SWBiological systems are capable of… pic.twitter.com/UdUYfqRXBS— Sakana AI (@SakanaAILabs) June 12, 2025
transformers/src/transformers/models/auto/tokenization_auto.py at 1d5296f2de31ecee4fdd789dc2b2fe068b320284 · huggingface/transformers
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - huggingface/transformers
AI Coding & Cloud | Meetup
This group started January 2016.We are about extraordinary advances in software creation, maintenance, and hosting.We are a gathering of good natured people for encouragement and support of what you do.This is your group! How you can help:1. Help to publicize events at work, with friends, and especi
Andrej Karpathy on Twitter / X
LLM Knowledge BasesSomething I'm finding very useful recently: using LLMs to build personal knowledge bases for various topics of research interest. In this way, a large fraction of my recent token throughput is going less into manipulating code, and more into manipulating…— Andrej Karpathy (@karpathy) April 2, 2026
Sessy - Open-source email observability for AWS SES
Track deliveries, bounces, opens, clicks, and complaints from AWS SES in a self-hosted dashboard you own.
Running inference in web extensions | The Mozilla Blog
Image generated by DALL*E We’re shipping a new API in Firefox Nightly that will let you use our Firefox AI runtime to run offline machine learning tasks
Personal information firehose · Adam Wiggins
My new research project asks whether a personal algorithm, inspired by social media, can help us filter our email, group chats, and other personal correspondence.
Personal information firehose · Adam Wiggins
My new research project asks whether a personal algorithm, inspired by social media, can help us filter our email, group chats, and other personal correspondence.
Introducing FlexOlmo: a new paradigm for language model training and data collaboration | Ai2
Explore how FlexOlmo enables collaborative language model training without sacrificing data privacy or control, introducing a new, flexible approach to building shared AI models.
The Kaitchup – AI on a Budget | Benjamin Marie | Substack
Weekly tutorials and news on adapting large language models (LLMs) to your tasks and hardware using the most recent techniques and models. The Kaitchup proposes a collection of 180+ AI notebooks regularly updated. Click to read The Kaitchup – AI on a Budget, by Benjamin Marie, a Substack publication with tens of thousands of subscribers.
Karpathy shares 'LLM Knowledge Base' architecture that bypasses RAG with an evolving markdown library maintained by AI
Karpathy proposes something simpler and more loosely, messily elegant than the typical enterprise solution of a vector database and RAG pipeline.
