Generative AI

I-JetBrains Ikhipha I-Mellum2: Imodeli Ye-12B MoE Yemisebenzi Esheshayo, Ekhethekile Kumapayipi AI Amamodeli Amaningi

I-JetBrains Ikhipha I-Mellum2: Imodeli Ye-12B MoE Yemisebenzi Esheshayo, Ekhethekile Kumapayipi AI Amamodeli Amaningi

I-JetBrains ikhiphe i-Mellum2, ivula izisindo ngaphansi kwelayisensi ye-Apache 2.0. Inguqulo yokuqala ye-Mellum bekuyimodeli eminyene ye-4B egxile ekuqedeni. I-Mellum2 ilandela: imodeli…
How to Speed ​​Up Transformer Training Using NVIDIA Apex (FusedAdam, FusedLayerNorm) and Native torch.amp

How to Speed ​​Up Transformer Training Using NVIDIA Apex (FusedAdam, FusedLayerNorm) and Native torch.amp

print("n### SECTION D: end-to-end Transformer (vanilla fp32 vs Apex fused + AMP) ###") VOCAB, D, NHEAD, LAYERS, SEQ, BATCH, STEPS…
Meet Memory OS: A 6-Layer Memory Stack Built on Hermes Agent

Meet Memory OS: A 6-Layer Memory Stack Built on Hermes Agent

Hermes Agent already remembers from every session. An open source agent from Nous Research ships with selected memory files and…
A Coding Implementation in Loguru for Designing Robust, Structured, Uniform, and Production-Ready Python Pipelines

A Coding Implementation in Loguru for Designing Robust, Structured, Uniform, and Production-Ready Python Pipelines

banner("1) logger.configure(): handlers + custom level + extra + patcher") mem = MemorySink() logger.configure( handlers=[ {"sink": sys.stderr, "format": console_formatter, "level":…
I-Trajectory Ikhipha I-Multi-LoRA Training Stack for Continuous Learning, Ibika i-2.81× Experiment-Throughput Gain

I-Trajectory Ikhipha I-Multi-LoRA Training Stack for Continuous Learning, Ibika i-2.81× Experiment-Throughput Gain

Isitaki se-Trajectory esisebenza ngesikhathi esisodwa se-multi-LoRA sibika inzuzo yokuhlola engu-2.81× ngaphezu kwe-RL yomqashi oyedwa, nayo yonke ikhodi endaweni ye-NovaSky-AI/SkyRL GitHub.…
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