這是舊版本，目前最新版本為b9994。 llama.cpp b9994 · 發行日期:
安裝檔 b8532
| 架構 | 類型 | 安裝範圍 | 檔案大小 | 下載 | SHA256 |
|---|---|---|---|---|---|
| 64位元 | ZIP → 免安裝版 | — | — | github.com | VirusTotal |
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更新紀錄
CUDA & CPU: support F32 kernel type for CONV_TRANSPOSE_2D (#17094)
- Refactor CUDA 2D transpose implementation to support multiple kernel types and improve parameter handling
- Introduced a conv2d_transpose_params struct for better parameter management.
- Updated conv2d_transpose_kernel to be templated for different kernel types (float and half).
- Modified ggml_cuda_conv_2d_transpose_p0 to handle both F16 and F32 kernel types.
- Enhanced test cases to validate functionality for both kernel types.
- Refactor test cases for 2D convolution transpose to support dynamic kernel types
- Updated test_conv_transpose_2d structure to improve parameter handling by reordering constructor arguments.
- Enhanced test case generation to iterate over kernel types, allowing for flexible testing of different configurations.
- Removed hardcoded kernel type instances in favor of a loop for better maintainability and scalability.
- Refactor ggml_compute_forward_conv_transpose_2d to support both F16 and F32 tensor types.
- Refactor conv2d transpose kernel to use a template for kernel type, enhancing flexibility for different data types.
Update test cases to include both F16 and F32 tensor types for comprehensive coverage.
- Update ggml/src/ggml-cuda/conv2d-transpose.cu
Co-authored-by: Aman Gupta amangupta052@gmail.com
- Update ggml/src/ggml-cpu/ggml-cpu.c
Co-authored-by: Aman Gupta amangupta052@gmail.com
- Refactor conv2d transpose implementation by removing the conv2d_transpose_params struct and dispatching with direct kernel launch.
- Enhance cpu conv2d transpose implementation by introducing a templated kernel type for improved flexibility with F16 and F32 data types.
Co-authored-by: Aman Gupta amangupta052@gmail.com
macOS/iOS:
- macOS Apple Silicon (arm64)
- macOS Intel (x64)
- iOS XCFramework
Linux:
- Ubuntu x64 (CPU)
- Ubuntu x64 (Vulkan)
- Ubuntu x64 (ROCm 7.2)
- Ubuntu s390x (CPU)
- Ubuntu x64 (OpenVINO)
Windows:
- Windows x64 (CPU)
- Windows arm64 (CPU)
- Windows x64 (CUDA 12) - CUDA 12.4 DLLs
- Windows x64 (CUDA 13) - CUDA 13.1 DLLs
- Windows x64 (Vulkan)
- Windows x64 (SYCL)
- Windows x64 (HIP)
openEuler:
- openEuler x86 (310p)
- openEuler x86 (910b, ACL Graph)
- openEuler aarch64 (310p)
- openEuler aarch64 (910b, ACL Graph)