tch-rs
ggml
Our great sponsors
tch-rs | ggml | |
---|---|---|
37 | 69 | |
3,843 | 9,642 | |
- | - | |
7.5 | 9.8 | |
5 days ago | 6 days ago | |
Rust | C | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tch-rs
- Tch-Rs
-
Llama2.rs: One-file Rust implementation of Llama2
I wanted to do something like this but then I would miss on proper CUDA acceleration and lose performance compared to using torchlib.
I wrote a forgettable llama implementation for https://github.com/LaurentMazare/tch-rs (pytorch's torchlib rust binding).
-
Playing Atari Games in OCaml
I first encountered OCaml's PyTorch bindings because apparently they generate a C wrapper around PyTorch's C++ API, and Rust's PyTorch bindings use OCaml's C wrapper. See: https://github.com/LaurentMazare/tch-rs
-
llm: a Rust crate/CLI for CPU inference of LLMs, including LLaMA, GPT-NeoX, GPT-J and more
You could try looking at the min-GPT example of tch-rs. I'd also strongly suggest watching Karpathy's video to understand what's going on.
-
Simply explained: How does GPT work?
If you pefer to see it in code there's a succint gpt implementation here https://github.com/LaurentMazare/tch-rs/blob/main/examples/m...
-
Will I ever need python again if I learn rust other than for AI stuff?
Rust is fully compatible w/ C bindings, so even Python libraries written in C can be easily set up to work in Rust (and have been). For example, see PyTorch Rust bindings, which actually works faster than in Python because all of the glue code around the C++ API is in Rust instead of Python.
-
A Rust client library for interacting with Microsoft Airsim https://github.com/Sollimann/airsim-client
Pytorch
- [D] HuggingFace in Julia or Rust ?
- This year I tried solving AoC using Rust, here are my impressions coming from Python!
-
[Help Needed] Deployment of torchscript using rust
I have looked into this a bit and found some crates which help in loading torchscript models called tch-rs
ggml
-
LLMs on your local Computer (Part 1)
git clone https://github.com/ggerganov/ggml cd ggml mkdir build cd build cmake .. make -j4 gpt-j ../examples/gpt-j/download-ggml-model.sh 6B
-
GGUF, the Long Way Around
Cool. I was just learning about GGUF by creating my own parser for it based on the spec https://github.com/ggerganov/ggml/blob/master/docs/gguf.md (for educational purposes)
-
Ask HN: People who switched from GPT to their own models. How was it?
If you don't care about the details of how those model servers work, then something that abstracts out the whole process like LM Studio or Ollama is all you need.
However, if you want to get into the weeds of how this actually works, I recommend you look up model quantization and some libraries like ggml[1] that actually do that for you.
[1] https://github.com/ggerganov/ggml
- GGUF File Format
-
Google just shipped libggml from llama-cpp into its Android AICore
Because the library is called ggml, but it supports gguf.
-
Q-Transformer
Apparently this guy like a bunch of others like https://github.com/ggerganov/ggml are implementing transformers from papers for people that want them. Pretty cool.
-
[P] Inference Vision Transformer (ViT) in plain C/C++ with ggml
You can access it here: https://github.com/staghado/vit.cpp It has been added to the ggml library on GitHub: https://github.com/ggerganov/ggml
-
Falcon 180B Released
https://github.com/ggerganov/ggml
One note is that prompt ingestion is extremely slow on CPU compared to GPU. So short prompts are fine (as tokens can be streamed once the prompt is ingested), but long prompts feel extremely sluggish.
-
Stable Diffusion in pure C/C++
I did a quick run under profiler and on my AVX2-laptop the slowest part (>50%) was matrix multiplication (sgemm).
In current version of GGML if OpenBLAS is enabled, they convert matrices to FP32 before running sgemm.
If OpenBLAS is disabled, on AVX2 plaftorm they convert FP16 to FP32 on every FMA operation, which even worse (due to repetition). After that, both ggml_vec_dot_f16 and ggml_vec_dot_f32 took first place in profiler.
Source: https://github.com/ggerganov/ggml/blob/master/src/ggml.c#L10...
-
Accessing Llama 2 from the command-line with the LLM-replicate plugin
For those getting started, the easiest one click installer I've used is Nomic.ai's gpt4all: https://gpt4all.io/
This runs with a simple GUI on Windows/Mac/Linux, leverages a fork of llama.cpp on the backend and supports GPU acceleration, and LLaMA, Falcon, MPT, and GPT-J models. It also has API/CLI bindings.
I just saw a slick new tool https://ollama.ai/ that will let you install a llama2-7b with a single `ollama run llama2` command that has a very simple 1-click installer for Apple Silicon Mac (but need to build from source for anything else atm). It looks like it only supports llamas OOTB but it also seems to use llama.cpp (via Go adapter) on the backend - it seemed to be CPU-only on my MBA, but I didn't poke too much and it's brand new, so we'll see.
For anyone on HN, they should probably be looking at https://github.com/ggerganov/llama.cpp and https://github.com/ggerganov/ggml directly. If you have a high-end Nvidia consumer card (3090/4090) I'd highly recommend looking into https://github.com/turboderp/exllama
For those generally confused, the r/LocalLLaMA wiki is a good place to start: https://www.reddit.com/r/LocalLLaMA/wiki/guide/
I've also been porting my own notes into a single location that tracks models, evals, and has guides focused on local models: https://llm-tracker.info/
What are some alternatives?
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
llama.cpp - LLM inference in C/C++
candle - Minimalist ML framework for Rust
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
cbindgen - A project for generating C bindings from Rust code
alpaca-lora - Instruct-tune LLaMA on consumer hardware
wtpsplit - Code for Where's the Point? Self-Supervised Multilingual Punctuation-Agnostic Sentence Segmentation
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
veloren - An open world, open source voxel RPG inspired by Dwarf Fortress and Cube World. This repository is a mirror. Please submit all PRs and issues on our GitLab page.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
burn - Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. [Moved to: https://github.com/Tracel-AI/burn]
llm - An ecosystem of Rust libraries for working with large language models