Also in that zip is `adv_app.py`, a single file example that shows nearly all the features of the lib, including detailed comments on how/why everything is the way it is. It's designed for both humans and LLMs to read.
OPEN SOURCE
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FastHTML Documentation Designed for LLMs and Humans
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Increasingly, docs are for LLMs to read, not just for humans to read. We're starting to explicitly design our docs to be great for *both* uses. As part of that, I'm aiming to include full markdown docs in our projects. FastHTML is the 1st! Here you go: https://
github.com/AnswerDotAI/fa
sthtml/raw/main/mds.zip
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Building Ecosystem Growth for Layer 0 Infrastructure Development
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Love to see a bigger ecosystem. Layer 0 needs people to grow
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Groq Supports Open Source Agent Hackathon with Andrew Ng
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There's great energy at the Open Source Agent Hackathon with @AndrewYNg at @agihouse_org
. Can't wait to see what our developer community builds on Groq today. -
Swift Development Transparency: Private Apple Bug Tracker Concerns
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“I do hope that someone goes back and critically evaluates why the discussion for "how can we make this work for Windows" is happening in a private, Apple-internal bug tracker. If you want to present Swift as a community project then it really ought to be tracked here and then
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Machine Learning Solves Newspaper Sudokus from Photos
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Using machine learning to solve newspaper Sudokus by taking a picture of the page: https://
github.com/Taiters/sudoku
-solver/blob/main/notebooks/explore.ipynb
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Meta Releases SAM 2 Open Source Visual Segmentation Model
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Segment Anything Model 2 (SAM 2) is a foundation model from Meta FAIR for promptable visual segmentation in images & videos.
— AI at Meta (@AIatMeta) 23 août 2024
Available now for anyone to build on for free, open source under an Apache license.
Try the demo ➡️ https://t.co/sTBToIR43x pic.twitter.com/iO1TlCej7xSegment Anything Model 2 (SAM 2) is a foundation model from Meta FAIR for promptable visual segmentation in images & videos. Available now for anyone to build on for free, open source under an Apache license. Try the demo https://
go.fb.me/ve0y8o -
DPO Preference Tuning with Ollama LLM Tutorial
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Link: https://
github.com/rasbt/LLMs-fro
m-scratch/blob/main/ch07/04_preference-tuning-with-dpo/create-preference-data-ollama.ipynb
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Building Large Language Models from Scratch Resource
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Build a large language model from scratch with this very cool resource
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Training LLM Engineers and Open-Sourcing Knowledge at Scale
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3 years ago we trained a big LLM together with +1000 people one of the part I'm most proud of is how it became the school for a generation of model training engineers as well as a strong push for sharing and open-sourcing knowledge in the field