gollum
llama.cpp
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gollum
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From slow to SIMD: A Go optimization story
I did a similar optimization via https://github.com/viterin/vek as the SIMD version. Some somewhat unscientific calculations showed a 10x improvement staying in float32: https://github.com/stillmatic/gollum/blob/07a9aa35d2517af8cf...
TBH my takeaway was that it was more useful to use smaller vectors as a representation
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Agency: Pure Go LangChain Alternative
I like Go a lot for working with OpenAI etc, it's 'just' API calls and Go is great at that. I've opensourced some bits here: https://github.com/stillmatic/gollum -- in particular, function dispatch (given a prompt, return an arbitrary Go struct) is really nice, as is a very fast in-memory KNN index.
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Introducing TypeChat from Microsoft
I've written a version of this in Golang: https://github.com/stillmatic/gollum/blob/main/dispatch.go
```go
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FANN: Vector Search in 200 Lines of Rust
I have gotten 10x speedups with SIMD on modern hardware. Goroutines make this actually fairly tricky, as you essentially have to process all the events and then sort the entire array, which is usually the bottleneck. The heap adds a small amount of complexity but is significantly more efficient, feels like good ROI.
https://github.com/stillmatic/gollum/blob/main/vectorstore.g...
llama.cpp
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IBM Granite: A Family of Open Foundation Models for Code Intelligence
if you can compile stuff, then looking at llama.cpp (what ollama uses) is also interesting: https://github.com/ggerganov/llama.cpp
the server is here: https://github.com/ggerganov/llama.cpp/tree/master/examples/...
And you can search for any GGUF on huggingface
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Ask HN: Affordable hardware for running local large language models?
Yes, Metal seems to allow a maximum of 1/2 of the RAM for one process, and 3/4 of the RAM allocated to the GPU overall. There’s a kernel hack to fix it, but that comes with the usual system integrity caveats. https://github.com/ggerganov/llama.cpp/discussions/2182
- Xmake: A modern C/C++ build tool
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Better and Faster Large Language Models via Multi-Token Prediction
For anyone interested in exploring this, llama.cpp has an example implementation here:
https://github.com/ggerganov/llama.cpp/tree/master/examples/...
- Llama.cpp Bfloat16 Support
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Fine-tune your first large language model (LLM) with LoRA, llama.cpp, and KitOps in 5 easy steps
Getting started with LLMs can be intimidating. In this tutorial we will show you how to fine-tune a large language model using LoRA, facilitated by tools like llama.cpp and KitOps.
- GGML Flash Attention support merged into llama.cpp
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Phi-3 Weights Released
well https://github.com/ggerganov/llama.cpp/issues/6849
- Lossless Acceleration of LLM via Adaptive N-Gram Parallel Decoding
- Llama.cpp Working on Support for Llama3
What are some alternatives?
CopilotKit - Build in-app AI chatbots 🤖, and AI-powered Textareas ✨, into react web apps. [Moved to: https://github.com/CopilotKit/CopilotKit]
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
ts-patch - Augment the TypeScript compiler to support extended functionality
gpt4all - gpt4all: run open-source LLMs anywhere
ai-agents-laravel - Build AI Agents for popular LLMs quick and easy in Laravel
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
voy - 🕸️🦀 A WASM vector similarity search written in Rust
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
TypeChat - TypeChat is a library that makes it easy to build natural language interfaces using types.
ggml - Tensor library for machine learning
Weaviate - Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM