On-device AI across mobile, embedded and edge for PyTorch
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PyTorch native post-training library
A PyTorch native platform for training generative AI models
Go ahead and axolotl questions
A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
Run frontier LLMs and VLMs locally on Qualcomm devices across NPU, GPU, and CPU with a few lines of code
Machine learning metrics for distributed, scalable PyTorch applications.
