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Stop vibe-debugging.
Plug Claude into your app's actual errors.
AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
...The project is built on the ggml backend, which allows efficient execution on CPUs and GPUs via backends like CUDA, Vulkan, Metal, OpenCL, and SYCL, making it suitable for everything from desktops to mobile devices. It includes options for ControlNet, LoRA models, upscaling via ESRGAN, and advanced sampling techniques, giving developers and users a rich toolkit for creative workflows.
Run a fast ChatGPT-like model locally on your device. This combines the LLaMA foundation model with an open reproduction of Stanford Alpaca a fine-tuning of the base model to obey instructions (akin to the RLHF used to train ChatGPT) and a set of modifications to llama.cpp to add a chat interface. Download the zip file corresponding to your operating system from the latest release. The weights are based on the published fine-tunes from alpaca-lora, converted back into a PyTorch checkpoint...