yano's picture

yano

yano2mch

AI & ML interests

LLM's for Roleplay and Story generation. And of course good image generation too.

Recent Activity

repliedto SeaWolf-AI's post about 7 hours ago
πŸ’» Data-center AI, now on a laptop: POCKET-Darwin-180B We're releasing a 4-bit GGUF build of Darwin-180B-RSI, #1 on seven official Hugging Face leaderboards (self-reported), that runs without a GPU. πŸ“¦ 360 GB β†’ 111 GB (4-bit GGUF, 4 files) πŸ–₯️ No GPU: one server CPU (16 threads) at 18.4–21.0 tokens/s πŸ’» RTX 5060 laptop (8 GB VRAM) + 32 GB RAM: 4.17 tokens/s 🧊 128 GB mini PC: whole model in memory, no GPU needed 🎯 MMLU-Pro, 2,000 questions, paired: original 87.65% = 4-bit 87.65% How? Β· Only ~3B of 180B parameters are active per token (10 of 512 experts) Β· llama.cpp streams just the needed experts from SSD, so 32 GB RAM is enough Β· Graft quantization: we took the proven Unsloth UD-Q4_K_XL base build and swapped in only the 300 tensors our RSI training changed (300/300 verified) Under the hood is Model-level Recursive Self-Improvement. The model solves verifiable problems, keeps only its own solutions that check out as correct, and trains on them. No human-written solutions or reasoning traces. Built for teams that can't send data to an external cloud (defense, finance, public sector) to run a top-tier model fully offline. πŸ“ Article: https://huggingface.co/blog/FINAL-Bench/data-center-ai-now-on-a-laptop-pocket-darwin-180b πŸ€— Model: https://huggingface.co/FINAL-Bench/POCKET-Darwin-180B-GGUF 🧬 Original: https://huggingface.co/FINAL-Bench/Darwin-180B-RSI #Darwin #RSI #GGUF #llamacpp #OnDevice #MoE
View all activity

Organizations

None yet