One line of Python to extend your LLM's context...

Your LLM is running out of memory at 128K tokens. Here is the fix. from nexusquant import nexusquant with nexusquant(model): output = model.generate(input_ids, max_new_tokens=500) That is the entire change. Before: 128K tokens, 40 GB KV cache memory on Llama-3-70B. After: 1.3M tokens, same 40 GB. 10x context window. Zero retraining. The pipeline compresses KV cache in four stages — normalization, Hadamard rotation, E8 lattice quantization, temporal delta coding — at 7x compression with -2.26% pe