Pruna 0.3.2: More OSS Algos, More Ways to Optimize
โข 5
AI & ML interests
Efficient machine learning for any model and hardware: pruning, quantization, compilation, and more.
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#1 opened about 4 hours ago
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minette-kaunismaki
ui-updates
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#1 opened about 4 hours ago
by minette-kaunismaki
minette-kaunismakiย
updated a
Space about 4 hours ago
begumcigย
updated a
Space 1 day ago
sdiazlorย
updated a
model 21 days ago
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140
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
- ~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
mehdiPrunaAIย
published a
model 22 days ago
mehdiPrunaAIย
updated a
model 22 days ago
Update README.md
๐ 1
#1 opened 23 days ago
by sdiazlor
Update README.md
๐ 1
#1 opened 23 days ago
by sdiazlor
davidberenstein1957ย
updated a
dataset 27 days ago
Post
183
As First Prune, the one-year Pruna OSS anniversary, is halfway.
Weโre sharing a recap blog post about our OSS journey โ how we started, what weโve built so far, and whatโs next.
Read it here: https://dev.to/pruna-ai/first-prune-celebrate-one-year-of-pruna-oss-50gp
Weโre sharing a recap blog post about our OSS journey โ how we started, what weโve built so far, and whatโs next.
Read it here: https://dev.to/pruna-ai/first-prune-celebrate-one-year-of-pruna-oss-50gp
Post
119
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:
โข Pick an open issue labelled "first-prune" and assign it to you
โข Submit your PR and mark it ready for review by April 30
โข Find out more in the PR template when you open a PR
Each merged PR scores 30 credits.
Letโs build something great together! Find your issue: https://github.com/PrunaAI/pruna/issues
What's First Prune:
If you contribute to open issues at our GitHub repo, you earn Pruna Inference API credits.
How you can participate:
โข Pick an open issue labelled "first-prune" and assign it to you
โข Submit your PR and mark it ready for review by April 30
โข Find out more in the PR template when you open a PR
Each merged PR scores 30 credits.
Letโs build something great together! Find your issue: https://github.com/PrunaAI/pruna/issues
Post
2618
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
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
Post
2890
๐จ Phare LLM benchmark V2: Reasoning models don't guarantee better security
Read the full blog here: https://huggingface.co/blog/davidberenstein1957/phare-llm-benchmark-v2
Read the full blog here: https://huggingface.co/blog/davidberenstein1957/phare-llm-benchmark-v2
davidberenstein1957ย
posted an update about 1 year ago
Post
640
Announcing RealPerformance, a dataset of functional issues of language models that mirrors failure patterns identified through rigorous testing in real LLM agents
https://huggingface.co/blog/davidberenstein1957/realperformance-llm-business-compliance
https://huggingface.co/blog/davidberenstein1957/realperformance-llm-business-compliance
davidberenstein1957ย
posted an update about 1 year ago
Post
426
๐จ 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
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
davidberenstein1957ย
posted an update about 1 year ago
Post
1782
I created a collection of FLUX.1 models but 4x faster PrunaAI/flux1-but-4x-faster-66c0b7340836dd7a55e9c0ea
davidberenstein1957ย
posted an update over 1 year ago
Post
1108
Good answers are not necessarily factual answers: an analysis of hallucination in leading LLMs
https://huggingface.co/blog/davidberenstein1957/phare-analysis-of-hallucination-in-leading-llms
https://huggingface.co/blog/davidberenstein1957/phare-analysis-of-hallucination-in-leading-llms
Post
3218
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.
๐ It is designed for a **large audience** including beginners, decision-makers, engineers, and researchers.
๐ 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! ๐
https://github.com/PrunaAI/awesome-ai-efficiency
๐ It is designed for a **large audience** including beginners, decision-makers, engineers, and researchers.
๐ 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! ๐
https://github.com/PrunaAI/awesome-ai-efficiency
- 2 replies