malaiwah/glm53-fixture-0.1B-fidelity-quant-int4-v1

GLM-5.3-Flash-0.1B fixture — candidate fidelity dataset, toy RTN-int4 routed experts (hidden form) The numbers in this dataset are meaningless as quantization quality. The weights are random (inference-optimization/GLM-5.3-Flash-0.1B-A0.1B is an architectural fixture), and the quantizer is deliberately crude. This exists so that step 3 of the three-step fidelity architecture has two real datasets to compare, and so that anyone can see what a candidate capture looks like next to… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/glm53-fixture-0.1B-fidelity-quant-int4-v1.