Is MLX the best Fine Tuning Framework?
🚀 Want to fine-tune AI models on your Mac without cloud services? As an ex-Ollama developer, I'll show you how to use Apple's MLX framework to fine-tune mod...
4. The Ollama Course - Using the CLI
Welcome back to the Ollama course! In this video, we dive deep into the command line interface (CLI) of Ollama, exploring all the powerful options and comman...
AI Hallucinations: Why Large Language Models Make Things Up (And How to Fix It) - kapa.ai - Instant AI answers to technical questions
Kapa.ai turns your knowledge base into a reliable and production-ready LLM-powered AI assistant that answers technical questions instantly. Trusted by 100+ startups and enterprises incl. OpenAI, Docker, Mapbox, Mixpanel and NextJS.
Building LLMs is probably not going be a brilliant business
The Netscapes of AI
Blaizzy/mlx-vlm: MLX-VLM is a package for running Vision LLMs locally on your Mac using MLX.
MLX-VLM is a package for running Vision LLMs locally on your Mac using MLX. - Blaizzy/mlx-vlm
2-fly-4-ai/V0-system-prompt
Contribute to 2-fly-4-ai/V0-system-prompt development by creating an account on GitHub.
exo-explore/exo: Run your own AI cluster at home with everyday devices 📱💻 🖥️⌚
Run your own AI cluster at home with everyday devices 📱💻 🖥️⌚ - exo-explore/exo
Everything I've learned so far about running local LLMs
Everything I’ve learned so far about running local LLMs
Chris Wellons shares detailed notes on his experience running local LLMs on Windows - though most of these tips apply to other operating systems as well. This is great, there's …
Creating a LLM-as-a-Judge That Drives Business Results –
A step-by-step guide with my learnings from 30+ AI implementations.
Creating a LLM-as-a-Judge that drives business results
Hamel Husain's sequel to [Your AI product needs evals](https://hamel.dev/blog/posts/evals/). This is _packed_ with hard-won actionable advice. Hamel warns against using scores on a 1-5 scale, instead promoting an alternative he …
You Should Probably Pay Attention to Tokenizers
Last week I was helping a friend of mine to get one of his new apps off the ground. I can’t speak much about it at the moment,
other than like most apps nowadays it has some AI sprinkled over …
LLMs don’t do formal reasoning - and that is a HUGE problem
Important new study from Apple
Training great LLMs entirely from ground up in the wilderness as a startup — Yi Tay
Chronicles of training strong LLMs from scratch in the wild
MIT spinoff Liquid debuts non-transformer AI models and they’re already state-of-the-art
The startup from MIT's CSAIL says its Liquid Foundation Models have smaller memory needs thanks to a post-transformer architecture.
What We Learned from a Year of Building with LLMs (Part I)
EvolutionaryScale
ESM3. Enabling scientists to understand, imagine, and create proteins.
txtai
txtai is an all-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
Florence 2 - The Best Small VLM Out There?
There is a new VLM on the scene and it comes with a dataset of 5Billion labels. The new model can do a variety of old world tasks like bounding boxes and segmentation along with newer LLM style captioning etc.
Paper: https://arxiv.org/pdf/2311.06242
HF Spaces Demo: https://huggingface.co/spaces/gokaygokay/Florence-2
Colab : https://drp.li/fGyMm
🕵️ Interested in building LLM Agents? Fill out the form below
Building LLM Agents Form: https://drp.li/dIMes
👨💻Github:
https://github.com/samwit/langchain-tutorials (updated)
https://github.com/samwit/llm-tutorials
⏱️Time Stamps:
00:00 Intro
00:13 Florence-2 Paper
02:19 Florence - 2 Architecture
03:20 Florence - 2 Detailed Image Captioning
03:41 Florence - 2 Visual Grounding
04:09 Florence - 2 Dense Region Caption
04:24 Florence - 2 Open Vocab Detection
06:01 Hugging Face Spaces Demo
10:41 Colab Florence - 2 Large Sample Usage
Training is not the same as chatting: ChatGPT and other LLMs don’t remember everything you say
I’m beginning to suspect that one of the most common misconceptions about LLMs such as ChatGPT involves how “training” works. A common complaint I see about these tools is that …
apple/OpenELM · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
GitHub - apple/corenet: CoreNet: A library for training deep neural networks
CoreNet: A library for training deep neural networks - apple/corenet
GitHub - apple/corenet: CoreNet: A library for training deep neural networks
CoreNet: A library for training deep neural networks - apple/corenet
openelm/README-pretraining.md
Apple released something big three hours ago, and I'm still trying to get my head around exactly what it is. The parent project is called CoreNet, described as "A library …
Command R
Command R is a conversational model that excels in language tasks and supports multiple languages, making it ideal for coding use cases that require instruction models. It responds well to preambles that follow a specific structure and format, enhancing its performance.
Models All The Way Down
Models All The Way Down
Introduction | Ragas
Ragas is a framework that helps you evaluate your Retrieval Augmented Generation (RAG) pipelines. RAG denotes a class of LLM applications that use external data to augment the LLM’s context. There are existing tools and frameworks that help you build these pipelines but evaluating it and quantifying your pipeline performance can be hard. This is where Ragas (RAG Assessment) comes in.
WeihaoTan/TWOSOME: Implementation of TWOSOME
flowersteam/Grounding_LLMs_with_online_RL: We perform functional grounding of LLMs' knowledge in BabyAI-Text