gschoeni

6 ms·

1.
by gschoeni 3mo ago
one of the oxen engineers here would love to hear about anything you ran into on the os product or platform! we've grown the team a bunch and are eager to learn what your perfect vcs looks like
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by gschoeni 4mo ago
Love this level of detail, thanks for sharing!
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by gschoeni 11mo ago
Wanted to share some learnings we had optimizing and deploying Qwen-Image-Edit at scale to replace Nano-Banana. The goal was to generate a product catalogue of 1.2m images, which would have cost $46k with Nano-Banana or GPT-Image-Edit. Qwen
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by gschoeni 1y ago
One of the maintainers of the Open Source project "Oxen" here. Our VCS scales for binary data better than git does, and was built to solve some of the problems with git-lfs and git-annex. We've had a few requests to integrate
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by gschoeni 1y ago
We're working on `oxen` to solve a lot of the problems we ran into with git or git-lfs. We have an open source CLI and server that mirrors git, but handles large files and mono repos with millions of files in a much more performant man
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by gschoeni 1y ago
How big are your datasets? Working on an Open Source git-lfs replacement called "oxen" if you are interested. https://github.com/Oxen-AI/Oxen
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by gschoeni 1y ago
FLUX.1-dev is one of the most widely fine-tuned models out there - but I couldn’t find a single, clean, end-to-end example that actually worked. So I wrote one. Enjoy!
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by gschoeni 2y ago
Over the past ~1.5 years I've been running a research paper club where we dive into interesting/foundational papers in AI/ML. So we naturally have come across a lot of the papers that lead up to DeepSeek-R1. While diving into
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Merkle Tree 101(ghost.oxen.ai)
1 points by gschoeni 2y ago|0 comments
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by gschoeni 2y ago
Right now the UI is only available through a VPC deployment. We are thinking about making the data grid / query interface embeddable or available through a library which would make it easy to self host.
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by gschoeni 2y ago
We're working on Oxen.ai which is an Open Source CLI and Server with Python bindings as well. Optimized for ML/AI workloads but works with any type of data and we see usage from game companies, bio, aerospace etc. Feel free to che
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by gschoeni 2y ago
Hey all, If you haven't seen the Oxen project yet, we have been building an open source unstructured data version control tool. We were inspired by the idea of making large machine learning datasets living & breathing assets that p
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by gschoeni 3y ago
Every Friday we pick a paper for our Paper Club and discuss it, here's the recap of yesterday's session on Mixtral 8x7B if anyone is interested! https://blog.oxen.ai/arxiv-dives-mixture-of-experts-moe-with...
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by gschoeni 3y ago
Yes it is! We meet every Friday at 10am PST and pick an Arxiv Paper to go over as a group. Feel free to join here: https://lu.ma/oxenbookclub
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by gschoeni 3y ago
We went over it in our Friday paper club before the holidays which helped me gain an intuition. https://blog.oxen.ai/mamba-linear-time-sequence-modeling-wit... I'm still not convinced on Mamba's performance on Nat
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by gschoeni 3y ago
I put together a reading list for Andrej Karpathy's intro to LLMs that would be helpful for all of the latest LLM and multi-modal architectures: https://blog.oxen.ai/reading-list-for-andrej-karpathys-intro...
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by gschoeni 3y ago
Have been studying the Mamba architecture all week and put together my notes here: https://blog.oxen.ai/mamba-linear-time-sequence-modeling-wit... I hadn't found a very satisfying explanation of the paper yet, and stil
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by gschoeni 3y ago
Hey all, I ran some experiments benchmarking fine-tuning ViT, ResNet50, and CLIP on a Facial Emotion Recognition dataset. I had read the original papers the past few weeks, but wanted to do some practical hands on use of the models themselv
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by gschoeni 3y ago
We've been working on a data version control system called "oxen" optimized for large unstructured datasets that we are seeing more and more with the advent of many of the generative AI techniques. Many of these datasets have
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by gschoeni 3y ago
Hey all, we had a lively group discussion today on the 2021 CLIP paper from OpenAI. Every Friday we've been going over the fundamentals of a lot of the state of the art techniques used in Machine Learning today. Hoping to learn a littl
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SUDS – A Guide to Structuring Unstructured Data(blog.oxen.ai)
3 points by gschoeni 3y ago|1 comments
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by gschoeni 3y ago
I've spent a decent amount of time indexing and formatting a lot of machine learning datasets that include images, audio, video, and text and wanted to propose a simple format that might help us standardize a format for the data with a
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by gschoeni 3y ago
Thanks for all the good work and all the pointers! Awesome stuff. Let me know if you would want to join us live on a Friday and go over some of your newer work or any recent papers you find interesting. Feel free to reach out at hello@oxen.
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Deep Dive into the Vision Transformers Paper(blog.oxen.ai)
40 points by gschoeni 3y ago|8 comments
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by gschoeni 3y ago
We have a reading club every Friday where we go over the fundamentals of a lot of the state of the art techniques used in Machine Learning today. Last week we dove into the "Vision Transformers" Paper from 2021 where the Google Br
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by gschoeni 3y ago
Oops, correct link here: https://blog.oxen.ai/reading-list-for-andrej-karpathys-intro...
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Reading List for Andrej Karpathy's "Intro to Large Language Models" Video(blog.oxen.ai)
75 points by gschoeni 3y ago|6 comments
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by gschoeni 3y ago
I loved Andrej's talk about in his "Busy person's intro to Large Language Models" video, so I decided to create a reading list to dive in deeper to a lot of the topics. I feel like he did a great job of describing the st
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by gschoeni 3y ago
I agree and like to think of it as machine inference vs machine learning: https://blog.oxen.ai/machine-inference-machine-learning/
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by gschoeni 3y ago
We have been working on an open source tool called "Oxen" that aims to tackle this problem! Would love for you to kick the tires and see if it works for your use case. We have a free version of the CLI, python library, and server

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