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I trained LLaMa from scratch

I trained the LLaMA model from scratch . Implemented RoPE, grouped-query attention, RMSNorm, SwiGLU, and KV cache with batched inference.Used Umar Jamil's great video on LLaMA for learning. Used three datasets for training: 1. tiny-shakespeare (character-level), to check that everything was working…

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  1. 2026-10-29 07:52 · r/deeplearning
    I trained LLaMa from scratch

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  1. I tested LFM2.5-24B-A2B vs Qwen3.6-35B-A3B on 75 fresh multi-step tool tasks. Qwen solved 91%, LFM2.5 49%, and LFM2.5 said "done" on most of its failures — r/LocalLLM
  2. Basalt (NVFP4) vs Unsloth Studio (llama.cpp IQ4_XS) — 5090 with 64GB RAM — r/LocalLLM
  3. Gemma 3 1B on the Nexus 5X (Directly on the Linux Kernel, No Android) — 2 GB RAM, 4.47 t/s — r/LocalLLM
  4. Nanbeige4.3-33B Q4 on a MacBook Pro M5 Max, mlx-lm vs llama.cpp vs Kapitsa, Prefill/Decode 512 to 32K range. — r/LocalLLaMA
  5. A 2013 Mac Pro runs a 35B model at 66 tok/s reading. The first benchmark I trusted was wrong by about 9x. — r/LocalLLM
  6. mtmd: enable video input support for LFM3 model family by tdakhran · Pull Request #31283 · ggml-org/llama.cpp — r/LocalLLaMA
  7. shura.cpp: a llama.cpp fork with a VRAM governor, so a 35B MoE can share one 16 GB card with the desktop you keep using — r/LocalLLM
  8. LiquidAI/LFM3-Omni-2B-GGUF — r/LocalLLaMA

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