navodPeiris/sri-lanka-case-law
Viewer • Updated • 14k • 41
Navod Peiris
navodPeiris
AI & ML interests
computer vision, Natural Language Processing
Recent Activity
updated a dataset 5 days ago
navodPeiris/sri-lanka-case-law published a dataset 5 days ago
navodPeiris/sri-lanka-case-law updated a model 14 days ago
navodPeiris/minilm-toxic-classifierOrganizations
updated a
dataset 5 days ago
published a
dataset 5 days ago
updated a
model 14 days ago
published a
model 14 days ago
updated 2
models about 2 months ago
published 2
models about 2 months ago
liked a
model 2 months ago
updated a
model 10 months ago
liked a
model 10 months ago
published a
model 10 months ago
liked a
dataset 11 months ago
liked a
model 11 months ago
updated a
model 11 months ago
published a
model 11 months ago
liked 2
models about 1 year ago
reacted to fdaudens's post with ❤️ about 1 year ago
Post
2714
⭐️ The AI Energy Score project just launched - this is a game-changer for making informed decisions about AI deployment.
You can now see exactly how much energy your chosen model will consume, with a simple 5-star rating system. Think appliance energy labels, but for AI.
Looking at transcription models on the leaderboard is fascinating: choosing between whisper-tiny or whisper-large-v3 can make a 7x difference. Real-time data on these tradeoffs changes everything.
166 models already evaluated across 10 different tasks, from text generation to image classification. The whole thing is public and you can submit your own models to test.
Why this matters:
- Teams can pick efficient models that still get the job done
- Developers can optimize for energy use from day one
- Organizations can finally predict their AI environmental impact
If you're building with AI at any scale, definitely worth checking out.
👉 leaderboard: https://lnkd.in/esrSxetj
👉 blog post: https://lnkd.in/eFJvzHi8
Huge work led by @sasha with @bgamazay @yjernite @sarahooker @regisss @meg
You can now see exactly how much energy your chosen model will consume, with a simple 5-star rating system. Think appliance energy labels, but for AI.
Looking at transcription models on the leaderboard is fascinating: choosing between whisper-tiny or whisper-large-v3 can make a 7x difference. Real-time data on these tradeoffs changes everything.
166 models already evaluated across 10 different tasks, from text generation to image classification. The whole thing is public and you can submit your own models to test.
Why this matters:
- Teams can pick efficient models that still get the job done
- Developers can optimize for energy use from day one
- Organizations can finally predict their AI environmental impact
If you're building with AI at any scale, definitely worth checking out.
👉 leaderboard: https://lnkd.in/esrSxetj
👉 blog post: https://lnkd.in/eFJvzHi8
Huge work led by @sasha with @bgamazay @yjernite @sarahooker @regisss @meg
- 1 reply
liked a
model over 1 year ago
