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🔄 In a Training Loop

MetrisVailore

Metris
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AI & ML interests

Building a new general architecture for LLMs https://huggingface.co/Dream-W

Recent Activity

reacted to alphabell-research's post with 👍 1 day ago
One number missing from LFM3's on-device story: memory at 256K context. Liquid AI reports 1.90 GB peak on iPhone 17 Pro at 32K. From the pinned config, f16 K/V cache alone would be 0.41 GB at 32K, 1.61 GB at 128K and 3.22 GB at 256K, before weights and runtime buffers. The chart shows the calculation, not a phone measurement. If you have run longer contexts on-device, share peak memory and time to first token here: https://huggingface.co/LiquidAI/LFM3-1.7B/discussions/5 Model: https://huggingface.co/LiquidAI/LFM3-1.7B
liked a dataset 2 days ago
OPENGCM/DeepArithmark-1
repliedto Banaxi-Tech's post 2 days ago
BananaMind 3 is going to be an comeback. Sorry for the BGA things ( i genuinely didnt know about nsa existing and yes I used aiiii) Were going to use our BananaMind 2.1 Unified architecture with some changes + NSA and some other stuff.
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Humanity's Last Hackathon's profile picture Dream W's profile picture Best Easy To Use SLM Leaderboard Testers (BETU SLM Leaderboard Testers)'s profile picture