You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Assuming that a Windows 10 machine can run this code, can this run.c lllama2 be modified to be complied to run inference mode on a Windows 10 machine?
I asked Google Gemini 1.5 Pro this question and this is Gemini's response:
Compiling and Running the Code on Windows 10
While the provided code appears to be primarily written in C, it includes some POSIX-specific elements like mmap and munmap which are not directly available on Windows 10. Therefore, running this code directly on Windows 10 would require some modifications and additional libraries.
Here's a potential approach:
Replacing POSIX Functions:
Memory Mapping:
Use the Windows API functions CreateFileMapping, MapViewOfFile, and UnmapViewOfFile to achieve similar functionality as mmap and munmap.
Libraries like Boost.Interprocess could also provide cross-platform memory mapping solutions.
Other Functions:
Review the code for other potential POSIX-specific functions and find equivalent Windows API functions or libraries.
Compiler and Libraries:
Compiler:
Use a C compiler compatible with Windows, such as Microsoft Visual C++, MinGW, or Clang.
Libraries:
Ensure any required libraries (e.g., for linear algebra operations) have Windows versions or alternatives.
Code Structure:
Conditional Compilation:
The code already utilizes #if defined _WIN32 blocks. Adapt these sections to incorporate the necessary Windows-specific implementations.
Consider creating separate source files for platform-specific code to maintain clarity.
Building and Running:
Use the chosen compiler and build system to compile the code into an executable.
Run the executable from the command line, providing the required arguments (checkpoint path, options).
Additional Considerations:
OpenMP: The code utilizes OpenMP for parallelization. Ensure you have a compatible OpenMP library and compiler flags set up for Windows.
Testing: Thoroughly test the modified code on Windows 10 to ensure functionality and performance.
Tools and Libraries:
Microsoft Visual Studio
MinGW
Clang
Boost C++ Libraries
OpenMP library for Windows
Disclaimer:
Modifying the code to run on Windows 10 requires some C programming and Windows API knowledge. This response provides a general direction, and specific implementation details may vary.
The text was updated successfully, but these errors were encountered:
Hi. According to Google Gemini Pro, compiling a Llama2.c model on a Windows
10 machine is "difficult" also because of high RAM memory requirements.
And "Dependency Hell" due to "libraries optimized for Linux". I apprehend
that the windows-compile task is beyond my experience and practical
ability. Can Windows run the Linux version of Llama2.c within a Windows
builtin Linux environment "MingW64 ~" prompt? Is that the same method as
what you originally proposed? Can you point to simple instructions printed
online?
Assuming that a Windows 10 machine can run this code, can this run.c lllama2 be modified to be complied to run inference mode on a Windows 10 machine?
I asked Google Gemini 1.5 Pro this question and this is Gemini's response:
Compiling and Running the Code on Windows 10
While the provided code appears to be primarily written in C, it includes some POSIX-specific elements like mmap and munmap which are not directly available on Windows 10. Therefore, running this code directly on Windows 10 would require some modifications and additional libraries.
Here's a potential approach:
Memory Mapping:
Use the Windows API functions CreateFileMapping, MapViewOfFile, and UnmapViewOfFile to achieve similar functionality as mmap and munmap.
Libraries like Boost.Interprocess could also provide cross-platform memory mapping solutions.
Other Functions:
Review the code for other potential POSIX-specific functions and find equivalent Windows API functions or libraries.
Compiler:
Use a C compiler compatible with Windows, such as Microsoft Visual C++, MinGW, or Clang.
Libraries:
Ensure any required libraries (e.g., for linear algebra operations) have Windows versions or alternatives.
Conditional Compilation:
The code already utilizes #if defined _WIN32 blocks. Adapt these sections to incorporate the necessary Windows-specific implementations.
Consider creating separate source files for platform-specific code to maintain clarity.
Use the chosen compiler and build system to compile the code into an executable.
Run the executable from the command line, providing the required arguments (checkpoint path, options).
Additional Considerations:
OpenMP: The code utilizes OpenMP for parallelization. Ensure you have a compatible OpenMP library and compiler flags set up for Windows.
Testing: Thoroughly test the modified code on Windows 10 to ensure functionality and performance.
Tools and Libraries:
Microsoft Visual Studio
MinGW
Clang
Boost C++ Libraries
OpenMP library for Windows
Disclaimer:
Modifying the code to run on Windows 10 requires some C programming and Windows API knowledge. This response provides a general direction, and specific implementation details may vary.
The text was updated successfully, but these errors were encountered: