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LLM model quantization (compression) toolkit with HW acceleration support for Nvidia, AMD, Intel GPU and Intel/AMD/Apple CPU via HF, vLLM, and SGLang.
Self-contained Python lib with zero-dependencies that give you a unified device properties for gpu, cpu, and npu. No more calling separate tools such as nvidia-smi or /proc/cpuinfo and parsing it yourself.
A (nicer) tokenizer you want to use for model inference and training: with all known peventable gotchas normalized or auto-fixed.
[ICLRW'26] EoRA: Fine-tuning-free Compensation for Compressed LLM with Eigenspace Low-Rank Approximation
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers.
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