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Source channel @githubtrending · Post #15432 · Jan 23

#jupyter_notebook#chinese_llm#chinese_nlp#finetune#generative_ai#instruct_gpt#instruction_set#llama#llm#lora#open_models#open_source#open_source_models#qlora AirLLM is a tool that lets you run very large AI models on computers with limited memory by using a smart layer-by-layer loading technique instead of traditional compression methods. You can run a 70-billion-parameter model on just 4GB of GPU memory, or even a 405-billion-parameter model on 8GB, without losing model quality. The benefit is that you can use powerful AI models on affordable hardware without expensive upgrades, and the tool also offers optional compression features that can speed up performance by up to 3 times while maintaining accuracy. https://github.com/lyogavin/airllm

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Tutto Elezioni

@tuttoelezioni · Post #1356 · 10/27/2025, 07:15 AM

#Argentina🇦🇷 #Parlamentari Risultati parziali. Camera dei deputati. Sezioni scrutinate: 108.125/108.992 (99,20%). 🟪 La Libertà Avanza (#LLA|Libertaristi di destra): 40,65% (64) 🟦 Forza Patria (#FP|Centrosinistra peronista): 24,31% (31) 🟦 Province Unite (#PU|Centro): 4,96% (5) 🟥 Fronte di Sinistra (#FITU|Trotskisti): 3,71% (3) 🟦 Fronte Prima il Tucumán (#FTP): 2,28% (2) 🟥 Fronte Civico per Santiago (#FCS): 1,23% (2) 🟦 Forza Giustizialista Mendoza (#FJM): 1,10% (1) 🟦 Forza Entre Ríos (#FER): 1,06% (2) 🟪 Proposta federale per il cambiamento (#PFC): 1,05% (0) Altri: 19,65% (17) N.B.: Tra parentesi sono indicati i seggi ottenuti. @TuttoElezioni