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Dipankar Sarkar PRO

dipankarsarkar
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https://www.dipankar.cc

AI & ML interests

Building the AI-native stack. Agents as infrastructure, safety as architecture, performance as plumbing. I publish the receipts: papers, datasets, demos.

Recent Activity

repliedto Banaxi-Tech's post about 1 hour ago
We're excited to release BananaMindBench Leaderboard, our leaderboard for BananaMind Base Bench 1.1. It measures model performance on a variety of different tasks: Language Completion Common sense too World Knowledge Context Tracking Quantitative Logical Reasoning Code Completion Each has a different score and 1 overall score. Submit your own model: https://huggingface.co/spaces/BananaMind/BananaMindBench-Leaderboard/discussions Check it out: https://huggingface.co/spaces/BananaMind/BananaMindBench-Leaderboard
repliedto appvoid's post about 1 hour ago
A Small Model is All You Need. Meet `palmer-006` (90M) After 3 years of experiments, we are finally releasing our flagship tiny model: **palmer-006**. If you are building for edge hardware, SBCs (Raspberry Pi, etc.), or low-power devices, this is for you. Inspired by Andrej Karpathy's idea of a self-contained "cognitive core," we wanted to see how much power we could pack into a sub-100M parameter footprint. 📊 **The cool part:** As of today, `palmer-006` takes the **🥈 2nd spot on ArithMark-3**, sitting only behind MobileLLM-R1-140M-base... while being **36% smaller**. It's a 90M parameter model hitting as a highly competitive baseline against 125M+ models. 🧠 **How we "Palmerized" it:** We believe in starting our experiments with the absolute strongest baseline possible. 1. Light fine-tuning on highly curated data 2. Model merging 3. Another light fine-tuning round 4. Adjusted Mamba for maximum token speed ⚡️ ⚠️ *Note: This is a foundational language model. It has not been instruction-tuned yet!* Also, since this needs instruction tuning next to become a chat assistant—**what dataset would you recommend we use for the instruct tune?** --- 🔗 **Quick Links & Info:** * **License:** Open for research, education, hobby, and modification! (For commercial use/hosted APIs, shoot an email to nosoyhackercodigo@gmail.com. *PS: Donators can claim a free commercial license!*) * **Attribution:** Built using AI tech from the Technology Innovation Institute (TII). Can't wait to see what you build at the edge. Let me know your prompt completions below! 👇 https://huggingface.co/appvoid/palmer-006
upvoted a paper about 2 hours ago
IndicTalk: A Large-Scale Persona-Based Multilingual Conversational Corpus for Indic Languages
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