#7298 ggml_cuda_init: found 1 CUDA devices (Total VRAM: 2047 MiB): Device 0: NVIDIA GeForce GTX 950, compute capability 5.2,

156.224**5 Posted at: 2 hours ago

ggml_cuda_init: found 1 CUDA devices (Total VRAM: 2047 MiB):
Device 0: NVIDIA GeForce GTX 950, compute capability 5.2, VMM: yes, VRAM: 2047 MiB
load_backend: loaded CUDA backend from I:\翻译\whisper-cpp\ggml-cuda.dll
load_backend: loaded CPU backend from I:\翻译\whisper-cpp\ggml-cpu-haswell.dll

Traceback (most recent call last):
File "videotrans\recognition\_cpp.py", line 124, in _exec
videotrans.configure.excepts.SpeechToTextError: ggml_cuda_init: found 1 CUDA devices (Total VRAM: 2047 MiB):
Device 0: NVIDIA GeForce GTX 950, compute capability 5.2, VMM: yes, VRAM: 2047 MiB
load_backend: loaded CUDA backend from I:\翻译\whisper-cpp\ggml-cuda.dll
load_backend: loaded CPU backend from I:\翻译\whisper-cpp\ggml-cpu-haswell.dll

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "videotrans\task\only_one.py", line 70, in run
File "videotrans\task\_stage_recogn.py", line 63, in recogn
File "videotrans\recognition\__init__.py", line 211, in run
File "videotrans\recognition\_base.py", line 98, in run
File "videotrans\recognition\_cpp.py", line 131, in _exec
videotrans.configure.excepts.SpeechToTextError: ggml_cuda_init: found 1 CUDA devices (Total VRAM: 2047 MiB):
Device 0: NVIDIA GeForce GTX 950, compute capability 5.2, VMM: yes, VRAM: 2047 MiB
load_backend: loaded CUDA backend from I:\翻译\whisper-cpp\ggml-cuda.dll
load_backend: loaded CPU backend from I:\翻译\whisper-cpp\ggml-cpu-haswell.dll

cfg=[TaskCfgVTT]当前工作模式: 翻译视频 单视频模式
原始输入文件名: I:/字幕/21/21.mp3,
输出结果保存到文件夹: I:/字幕/21/21-mp3,
临时文件夹: I:/翻译/tmp/28016/e726707a50
未选 清理已存在
未启用CUDA加速
未选 降噪
语音识别:Whisper.cpp(Win内置), ggml-large-v3.bin, 发音语言: 韩语, 断句方式:默认断句
翻译渠道:Hy-MT2-1.8B(内置),原始语言:韩语,目标语言:简体中文, 已选 发送完整字幕
未选 配音角色,不进行配音
字幕: 嵌入软字幕
代理地址:http://127.0.0.1:7897


=
system:Windows-10-10.0.19045-SP0
version:v4.10
frozen:True
language:zh
root_dir:I:/翻译

1 Replies

#1 DeepSeek reply at 2 hours ago

核心原因是:Whisper.cpp 渠道的 CUDA 后端在初始化时失败,且你的 GPU 显存仅 2GB,无法支撑 large-v3 模型运行。

日志显示 未启用CUDA加速,但 Whisper.cpp 仍然尝试加载 CUDA 后端(ggml-cuda.dll),GTX 950 显存只有 2047 MiB,而 ggml-large-v3.bin 模型体积数 GB,GPU 显存和计算能力均不足,导致初始化后任务中断。
另外你的版本是 v4.10,知识库针对的是 v4.12,建议先升级。

请按以下步骤处理:

  1. 改用 faster-whisper(内置) 渠道(默认推荐),并提供可用的 CUDA 加速环境。若 CUDA 环境不完整(CUDA 12.8 + cuDNN 9.11 以上),则不要勾选 CUDA 加速,改用 CPU 运行,但速度会明显变慢。
  2. 更换更小的模型。在语音识别模型下拉中不要选 large-v3,改用 smallbaselarge-v3 需约 8GB 显存)。2GB 显存建议不要使用 GPU 加速。
  3. 如果一定要用 Whisper.cpp,请到软件目录/models中确认所用的 .bin 为较小的模型(如 ggml-small.bin),并避免使用 CUDA 后端。
  4. 建议将软件升级到最新 v4.12,并重新下载完整包或补丁包覆盖。

请查阅相关文档:

Thinking...
Post Your Reply
If you have more than 50 messages, you will no longer receive an automatic reply. Please ask a new question!
Open source and free maintenance is not easy. If this project is helpful to you, please consider making a small donation to help the project continue to maintain and update.

Dondate via ko-fi.com

Related resource