Sreerag M./ ശ്രീരാഗ് എം. @sreagm
Joined November 2018-
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For years, we've been saying that bigger isn't always better for AI and that smaller specialized models are usually faster, cheaper and more accurate for your specific constraints. So super happy to release the long-overdue capability of finding the best model based on size on…
A real-time object detector much faster and accurate than YOLO with Apache 2.0 license just landed to @huggingface transformers 🔥 D-FINE is the sota real-time object detector that runs on T4 (free Colab) 🤩 Keep reading for the paper explainer, notebooks & demo 👀
Information -> Embed -> Store | Query -> Embed -> Retrieve -> Augment -> Generate colab.research.google.com/drive/1qMhhxFd…
@GrigoryEvko Lot's of hosted models at darkspark.dev, and a public pip package coming soon! (that particular viz is only in my local dev version, also coming soon...)
Today OpenAI announced o3, its next-gen reasoning model. We've worked with OpenAI to test it on ARC-AGI, and we believe it represents a significant breakthrough in getting AI to adapt to novel tasks. It scores 75.7% on the semi-private eval in low-compute mode (for $20 per task…
We are announcing that PyTorch will stop publishing Anaconda packages on PyTorch’s official anaconda channels. For more information, please refer to the following post on dev-discuss: dev-discuss.pytorch.org/t/pytorch-depr…
I made some visual aids about modular duality for a workshop presentation and I wanted to share them here too. First, vanilla gradient descent does not type check! Gradients have the right units to dot product with weights but not to subtract from weights. (1/4)
Qwen and DeepSeek don't get nearly as much applause and attention as they deserve.
Qwen and DeepSeek don't get nearly as much applause and attention as they deserve.
Today at 4:30p at #ECCV2024 in Milan, I'll present EgoPet, the first large collection of egocentric videos from animals' perspective! If you're curious about what we can learn from animals, come to poster #92! Project Website: amirbar.net/egopet/
I published a small blurb about some very tiny timm test vision models I've recently shared on the @huggingface Hub. These are not 'smol' in the 'here's a 100+M to 1B param LM' sense, but small in the 200K to 1M param way, so *really* small. huggingface.co/blog/rwightman…
hacked bitnet for finetuning, ended up with a 74mb file. It talks fine at 198 tokens per second on just 1 cpu core. Basically witchcraft. opensourcing later via @skunkworks_ai base here: huggingface.co/nisten/Biggie-…
Autoregressive Model Beats Diffusion Llama for Scalable Image Generation We introduce LlamaGen, a new family of image generation models that apply original ``next-token prediction'' paradigm of large language models to visual generation domain. It is an affirmative
New paper: The Platonic Representation Hypothesis In which we posit that _different_ foundation models are converging to the _same_ representation of reality. paper: arxiv.org/abs/2405.07987 website: phillipi.github.io/prh/ code: github.com/minyoungg/plat… 1/8
Finished my GPU homework from 10 Minute Physics in @JuliaLanguage 🚀 The numerical method is PBD. My last math preprint shows the convergence of PBD in overdamped case (not shown here, it's my next homework😜) arxiv.org/abs/2310.01215 All credits go to matthias-research.github.io/pages/tenMinut…
Day 24 of llm.c: we now do multi-GPU training, in bfloat16, with flash attention, directly in ~3000 lines of C/CUDA, and it is FAST! 🚀 We're running ~7% faster than PyTorch nightly, with no asterisks, i.e. this baseline includes all modern & standard bells-and-whistles: mixed…
Is there anything like Comfy workflows for general computer vision? Not just for generative models.
Here is the full email. Interesting glimpse at the vulnerability and weaknesses of a mega-corporation that seems (at least to me) invulnerable.
Here is the full email. Interesting glimpse at the vulnerability and weaknesses of a mega-corporation that seems (at least to me) invulnerable. https://t.co/GnhWBAJKhv
*Alice goes to a differentiable wonderland!* 🔥 I published a short free book on the design of neural networks, from convolutions to transformers, SSMs, and a few other topics. As a bonus, I tried to make it looking nice - any feedback is appreciated! sscardapane.it/alice-book
Seminal paper by von Neumann et al on how to build a computer cs.unc.edu/~adyilie/comp2…
Our computer vision textbook is released! Foundations of Computer Vision with Antonio Torralba and Bill Freeman mitpress.mit.edu/9780262048972/… It’s been in the works for >10 years. Covers everything from linear filters and camera optics to diffusion models and radiance fields. 1/4
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