fix(ci): Fix release by updating macos runner image to non-deprecated version by @abetlen in afedfc888462f9a6e809dc9455eb3b663764cc3f fix(server): add missing await statements for async exit_stack handling by @gjpower in #1858 [0.3.4] fix(ci): Build wheels for macos 13-15, cuda 12...
fix(docker): Fix GGML_CUDA param by @olivierdebauche in #1633 fix(docker): Update Dockerfile build options from LLAMA_ to GGML_ by @olivierdebauche in #1634 feat: FreeBSD compatibility by @yurivict in #1635 [0.2.84] feat: Update llama.cpp to ggerganov/llama.cpp@4730faca618ff9cee07...
✅ 检查Python 版本 (python --version) ✅ 安装依赖 (sudo apt install cmake make g++ python3-dev) ✅ 清除缓存并强制重新安装 (pip install --no-cache-dir llama-cpp-python) ✅ 尝试CUDA 版本(如果有 GPU) ✅ 使用预编译版本 (pip install llama-cpp-python --prefer-binary)二...
--extra-index-url=https://abetlen.github.io/llama-cpp-python/whl/$CUDA_VERSION \ llama-cpp-python # 对于 Metal (MPS) export GGML_METAL=on pip install llama-cpp-python 运行示例 安装完成后,你可以通过下面的命令来测试 Llama-CPP-Python 是否正确安装: ...
ggml_init_cublas: found 1 CUDA devices: Device 0: NVIDIA GeForce RTX 4090, compute capability 6.1, VMM: yes llama_model_loader: loaded meta data with 19 key-value pairs and 291 tensors from llama-2-7b-chat.Q8_0.gguf (version GGUF V2) ...
ERROR: llama_cpp_python_cuda-0.2.6+cu117-cp310-cp310-manylinux_2_31_x86_64.whl is not a supported wheel on this platform. System: Ubuntu 22.04 CUDA: 11.7 Python: 3.10 In the past, this was caused by trying to use the wrong Python version. You might want to make absolutely sure th...
pip install llama-cpp-python \ --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/<cuda-version> Where<cuda-version>is one of the following: cu121: CUDA 12.1 cu122: CUDA 12.2 cu123: CUDA 12.3 cu124: CUDA 12.4 For example, to install the CUDA 12.1 wheel: pip install ...
ERROR: llama_cpp_python_cuda-0.2.6+cu117-cp310-cp310-manylinux_2_31_x86_64.whl is not a supported wheel on this platform. Ignoring llama-cpp-python-cuda: markers 'platform_system == "Windows"' don't match your environment ERROR: llama_cpp_python_cuda-0.2.6+cu117-cp310-cp310-manyl...
llama_kv_cache_init: CUDA0 KV buffer size = 328.00 MiB llama_kv_cache_init: CUDA1 KV buffer size = 312.00 MiB llama_new_context_with_model: KV self size = 640.00 MiB, K (f16): 320.00 MiB, V (f16): 320.00 MiB llama_new_context_with_model: CUDA_Host output buffer size = 0.52 M...
如果仅在 CPU 上运行,可以直接使用 pip install llama-cpp-python 进行安装。 否则,请确保系统已安装 CUDA,可以通过 nvcc --version 检查。 GGUF 以bartowski/Mistral-7B-Instruct-v0.3-GGUF 为例进行演示。你将在模型界面查看到以下信息:可以看到 4-bit 量化有 IQ4_XS,Q4_K_S, IQ4_NL,Q4_K_M 四种,...