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Create tech stack docs (techstack.yml and techstack.md) #1

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@stack-file stack-file bot commented Feb 11, 2024

Adding tech stack documentation to allow anyone to easily see what is being used in this repo without digging through config files. Two files are being added: techstack.yml and techstack.md. techstack.yml contains data on all the technologies being used in this repo. techstack.md is a visualization of the YML file and displays the tech stack data in a pretty Markdown file.

💡 Protip: techstack.md contains a comment at the top of the file that the following README snippet (with and without the logos) at the top of the file as a comment:

<--- Readme.md Snippet without images Start --->

Tech Stack

kclhi/llama.cpp is built on the following main stack:

Full tech stack here

<--- Readme.md Snippet without images End --->

Get the code:

## Tech Stack
kclhi/llama.cpp is built on the following main stack:

- [C lang](http://en.wikipedia.org/wiki/C_(programming_language)) – Languages
- [C++](http://www.cplusplus.com/) – Languages
- [Objective-C](https://developer.apple.com/library/mac/documentation/Cocoa/Conceptual/ProgrammingWithObjectiveC/Introduction/Introduction.html) – Languages
- [Python](https://www.python.org) – Languages
- [Swift](https://developer.apple.com/swift/) – Languages
- [CMake](http://www.cmake.org/) – Java Build Tools
- [Docker](https://www.docker.com/) – Virtual Machine Platforms & Containers
- [GitHub Actions](https://github.com/features/actions) – Continuous Integration
- [Nix](http://nixos.org/nix) – Package Managers
- [CUDA](http://www.nvidia.com/object/cuda_home_new.html) – Machine Learning Tools
- [NumPy](http://www.numpy.org/) – Data Science Tools
- [Shell](https://en.wikipedia.org/wiki/Shell_script) – Shells

Full tech stack [here](/techstack.md)

<--- Readme.md Snippet with images Start --->

Tech Stack

kclhi/llama.cpp is built on the following main stack:

Full tech stack here

<--- Readme.md Snippet with images End --->

Get the code:

## Tech Stack
kclhi/llama.cpp is built on the following main stack:

- <img width='25' height='25' src='https://img.stackshare.io/no-img-open-source.png' alt='C lang'/> [C lang](http://en.wikipedia.org/wiki/C_(programming_language)) – Languages
- <img width='25' height='25' src='https://img.stackshare.io/service/1049/cplusplus.png' alt='C++'/> [C++](http://www.cplusplus.com/) – Languages
- <img width='25' height='25' src='https://img.stackshare.io/service/1008/xcode.png' alt='Objective-C'/> [Objective-C](https://developer.apple.com/library/mac/documentation/Cocoa/Conceptual/ProgrammingWithObjectiveC/Introduction/Introduction.html) – Languages
- <img width='25' height='25' src='https://img.stackshare.io/service/993/pUBY5pVj.png' alt='Python'/> [Python](https://www.python.org) – Languages
- <img width='25' height='25' src='https://img.stackshare.io/service/1009/tuHsaI2U.png' alt='Swift'/> [Swift](https://developer.apple.com/swift/) – Languages
- <img width='25' height='25' src='https://img.stackshare.io/service/2424/0UlUI_y1_400x400.jpg' alt='CMake'/> [CMake](http://www.cmake.org/) – Java Build Tools
- <img width='25' height='25' src='https://img.stackshare.io/service/586/n4u37v9t_400x400.png' alt='Docker'/> [Docker](https://www.docker.com/) – Virtual Machine Platforms & Containers
- <img width='25' height='25' src='https://img.stackshare.io/service/11563/actions.png' alt='GitHub Actions'/> [GitHub Actions](https://github.com/features/actions) – Continuous Integration
- <img width='25' height='25' src='https://img.stackshare.io/service/4348/ET9J1uY-_400x400.png' alt='Nix'/> [Nix](http://nixos.org/nix) – Package Managers
- <img width='25' height='25' src='https://img.stackshare.io/service/2836/LUOWehvo_400x400.jpeg' alt='CUDA'/> [CUDA](http://www.nvidia.com/object/cuda_home_new.html) – Machine Learning Tools
- <img width='25' height='25' src='https://img.stackshare.io/service/2179/default_332f874a2edb2686f578aa6389313efcea1eec41.png' alt='NumPy'/> [NumPy](http://www.numpy.org/) – Data Science Tools
- <img width='25' height='25' src='https://img.stackshare.io/service/4631/default_c2062d40130562bdc836c13dbca02d318205a962.png' alt='Shell'/> [Shell](https://en.wikipedia.org/wiki/Shell_script) – Shells

Full tech stack [here](/techstack.md)

martinchapman pushed a commit that referenced this pull request Sep 6, 2024
* [example] batched-bench "segmentation fault"

When `llama-batched-bench` is invoked _without_ setting `-npl`, "number
of parallel prompts", it segfaults.

The segfault is caused by invoking `max_element()` on a zero-length
vector, `n_pl`

This commit addresses that by first checking to see if the number of
parallel prompts is zero, and if so sets the maximum sequence size to 1;
otherwise, sets it to the original, the result of `max_element()`.

Fixes, when running `lldb build/bin/llama-batched-bench -- -m models/Meta-Llama-3-8B.gguf`

```
* thread #1, queue = 'com.apple.main-thread', stop reason = EXC_BAD_ACCESS (code=1, address=0x0)
    frame #0: 0x000000010000366c llama-batched-bench`main(argc=3, argv=0x000000016fdff268) at batched-bench.cpp:72:28
   69  	    llama_context_params ctx_params = llama_context_params_from_gpt_params(params);
   70
   71  	    // ensure enough sequences are available
-> 72  	    ctx_params.n_seq_max = *std::max_element(n_pl.begin(), n_pl.end());
```

* Update examples/batched-bench/batched-bench.cpp

Co-authored-by: compilade <git@compilade.net>

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: compilade <git@compilade.net>
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