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Tag: cuda

  • Tensor Addition with PyTorch and CUDA

    Tensor Addition with PyTorch and CUDA Tensor Addition is a fundamental operation in tensor algebra. It involves adding corresponding elements of two tensors that have the same shape, resulting in a new tensor of the same shape where each element is the sum of the corresponding elements of the input tensors. When performed on a Read more

  • RAG with locally running LLM

    Sample code to enable running the LLM locally. This will involve using a local LLM instead of OpenAI. Key Changes: To run this code with a local LLM: Important Considerations: Read more

  • Tensor

    PyTorch’s fundamental data structure is the Tensor. It’s the central object for numerical computation in PyTorch, analogous to NumPy’s ndarray but with added capabilities for GPU acceleration and automatic differentiation (crucial for deep learning). Here’s a breakdown of PyTorch’s data structure landscape, with the Tensor at the core: 1. Tensors (torch.Tensor) 2. NumPy Arrays (numpy.ndarray) Read more