AI & ML interests

Efficient machine learning for any model and hardware: pruning, quantization, compilation, and more.

Recent Activity

sdiazlorย  updated a model 4 days ago
PrunaAI/PrunaVAED
mehdiPrunaAIย  published a model 5 days ago
PrunaAI/PrunaVAED
mehdiPrunaAIย  updated a model 5 days ago
PrunaAI/PrunaVAED
View all activity

Articles

sdiazlorย 
posted an update 5 days ago
view post
Post
115
Hey! We've released PrunaVAED, a drop-in replacement decoder for LTX-2.3

- ~1.7-2.1x faster decoder & ~50% lower peak VRAM
- Near-original visual quality & no changes to the latent encoding

Check it here: PrunaAI/PrunaVAED
sdiazlorย 
in PrunaAI/PrunaVAED 6 days ago
sdiazlorย 
posted an update 4 months ago
sdiazlorย 
posted an update 4 months ago
view post
Post
116
Pruna OSS is turning 1! To mark this milestone, we're launching the First Prune initiative.

What's First Prune:
If you contribute to open issues at our GitHub repo, you earn Pruna Inference API credits.

How you can participate:
โ€ข Pick an open issue labelled "first-prune" and assign it to you
โ€ข Submit your PR and mark it ready for review by April 30
โ€ข Find out more in the PR template when you open a PR

Each merged PR scores 30 credits.

Letโ€™s build something great together! Find your issue: https://github.com/PrunaAI/pruna/issues
sdiazlorย 
posted an update 5 months ago
view post
Post
2616
More OSS than ever with the latest pruna 0.3.2 release. It extends existing algorithm families, such as compilers, kernels, and pruners, and adds new ones, including decoders, distillers, enhancers, and recoverers. But it's not only a collection of algorithms; instead, you can easily combine them to get the biggest efficiency win.

Read the full blog here: https://huggingface.co/blog/PrunaAI/pruna-0-3-2-open-source-optimization-algorithms
davidberenstein1957ย 
posted an update 8 months ago
davidberenstein1957ย 
posted an update about 1 year ago
davidberenstein1957ย 
posted an update about 1 year ago
view post
Post
424
๐Ÿšจ LLMs recognise bias but also reproduce harmful stereotypes: an analysis of bias in leading LLMs

I've written a new entry in our series on the Giskard, BPIFrance and Google Deepmind Phare benchmark(phare.giskard.ai).

This time it covers bias: https://huggingface.co/blog/davidberenstein1957/llms-recognise-bias-but-also-produce-stereotypes

Previous entry on hallucinations: https://huggingface.co/blog/davidberenstein1957/phare-analysis-of-hallucination-in-leading-llms
  • 1 reply
ยท
davidberenstein1957ย 
posted an update about 1 year ago
davidberenstein1957ย 
posted an update about 1 year ago
sharpenbย 
posted an update about 1 year ago
view post
Post
3217
How to learn about efficient AI? - Happy to announce the Awesome AI Efficiency repo that gathers a curated list of 100+ materials to understand the challenges and solutions in making AI faster, smaller, cheaper, greener.

๐Ÿš€ It is designed for a **large audience** including beginners, decision-makers, engineers, and researchers.
๐Ÿ“š It contains **diverse materials** with newspaper articles, blogs, tools, tech reports, research papers, books, and lectures.

This is an ongoing project. Do not hesitate to share your feedback/suggestions and star the repo! ๐ŸŒŸ

https://github.com/PrunaAI/awesome-ai-efficiency
  • 2 replies
ยท
davidberenstein1957ย 
posted an update over 1 year ago
view post
Post
2290
๐Ÿ”ฅ Announcing FLUX-Juiced: The Fastest Image Generation Endpoint (2.6x faster)!

Optimisations are widely applied and can reduce inference time, but their impact on quality often remains unclear, so we decided to challenge the status quo and create our own optimised version of FLUX.1[dev] called FLUX-juiced.

Blog: https://huggingface.co/blog/PrunaAI/flux-fastest-image-generation-endpoint
davidberenstein1957ย 
posted an update over 1 year ago
davidberenstein1957ย 
posted an update over 1 year ago
view post
Post
1415
RealHarm: A Collection of Real-World Language Model Application Failure

I'm David from Giskard, and we work on securing your Agents.
Today, we are launching RealHarm: a dataset of real-world problematic interactions with AI agents, drawn from publicly reported incidents.

Check out the dataset and paper: https://realharm.giskard.ai/