Nirca Mini is a small chat model trained from scratch, with ternary weights: its linear layers' weights are -1, 0 or +1, with a scale and a bias for each block of 128 weights. It reads and writes bytes, so it needs no tokenizer. It - Trained from scratch in ternary, with quantization-aware training from almost the very start; the ternary weights were learned in training, not quantized after. Nirca was inspired by mini-AGI, and its architecture is Try it in your browser (WebGPU): https://tg-techie-agents.github.io/nirca-mini-webgpu/mini/ This card is written by program from the checkpoint's own record, at step 122,203 (4,592,602,367 tokens seen). a mixture of experts (MLX's 2-bit affine…