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Products that do what Grammar Generator App for Llama.cpp does

llama.cpp added context-free grammar guided generation functionality. It requires passing a file in a derivative of BNF notation, which gets messy very quickly for things like JSON. To improve the experience, we built a small compiler from TypeScript interfaces to the grammar file format and have it hosted in a little browser app. See more in discussion at https://github.com/ggerganov/llama.cpp/discussions/2494

  1. 1

    Llama 405B-level performance, at a fraction of the cost

    2024

  2. 2
    Llama 2263

    The next generation of Meta's open source LLM

    2023

  3. 3LC

    Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…

    2023 · github.com

  4. 4

    AI-powered coding assistant by Meta

    2024

  5. 5AC
  6. 6
    LLaMA118

    A foundational, 65-billion-parameter large language model

    2023

  7. 7LT

    2023 · github.com

  8. 8FL

    I've been playing around with https://github.com/zphang/minimal-llama/ and https://github.com/tloen/alpaca-lora/blob/main/finetune.py, and wanted to create a simple UI where you can just paste text, tweak the parameters, and finetune the model quickly using a modern GPU. To prepare the data, simply separate your text with two blank lines. There's an inference tab, so you can test how the tuned model behaves. This is my first foray into the world of LLM finetuning, Python, Torch, Transformers, LoRA, PEFT, and Gradio. Enjoy!

    2023 · github.com

  9. 9

    New, performant version of Meta's LLM for code generation

    2024

  10. 10LD
  11. 11LE

    Author here. I just wanted a quick and easy way to easily submit strings to a REST API and get back the embedding vectors in JSON using Llama2 and other similar LLMs, so I put this together over the past couple days. It's very quick and easy to set up and totally self-contained and self-hosted. You can easily add new models to it by simply adding the HuggingFace URL to the GGML format model weights. Two models are included by default, and these are automatically downloaded the first time it's run. It lets you not only submit text strings and get back the embeddings, but also to compare two…

    2023 · github.com

  12. 12OS

    Stateful load balancer customized for llama.cpp (with a reverse proxy).

    2024 · github.com

  13. 13
    Llama312

    3.1-405B: an open source model to rival GPT-4o / Claude-3.5

    2024

  14. 14KR

    I discovered that in LLM inference, keys and values in the KV cache have very different quantization sensitivities. Keys need higher precision than values to maintain quality. I patched llama.cpp to enable different bit-widths for keys vs. values on Apple Silicon. The results are surprising: - K8V4 (8-bit keys, 4-bit values): 59% memory reduction with only 0.86% perplexity loss - K4V8 (4-bit keys, 8-bit values): 59% memory reduction but 6.06% perplexity loss - The configurations use the same number of bits, but K8V4 is 7× better for quality This means you can run LLMs with 2-3× longer…

    2025 · github.com

  15. 15FT

    I wrote a small local tool to transcribe audio notes (Whisper/Parakeet). Code: https://github.com/bilawalriaz/lazy-notes I wanted to process raw transcripts locally without OpenRouter. Llama 3.2 3B with a prompt was decent but incomplete, so I tried SFT. I fine-tuned Llama 3.2 3B to clean/analyze dictation and emit structured JSON (title, tags, entities, dates, actions). Data: 13 real memos → Kimi K2 gold JSON → ~40k synthetic + gold; keys canonicalized. Chutes.ai (5k req/day). Training: RTX 4090 24GB, ~4h, LoRA (r=128, α=128, dropout=0.05), max seq 2048,…

    2025 · bilawal.net

  16. 16UC

    Hi HN, Code Llama was released, but we noticed a ton of questions in the main thread about how/where to use it — not just from an API or the terminal, but in your own codebase as a drop-in replacement for Copilot Chat. Without this, developers don't get much utility from the model. This concern is also important because benchmarks like HumanEval don't perfectly reflect the quality of responses. There's likely to be a flurry of improvements to coding models in the coming months, and rather than relying on the benchmarks to evaluate them, the community will get better feedback from people…

    2023 · continue.dev

  17. 17AF

    We believe that AI should be fully open source and part of the collective knowledge. The original LLaMA code is GPL licensed which means any project using it must also be released under GPL. This "taints" any other code and prevents meaningful academic and commercial use. Lit-LLaMA solves that for good.

    2023 · github.com

  18. 18PG

    This proof-of-concept project combines: - Flutter, from Google; - ClojureDart, port of Clojure to Dart from Tensegritics; and - Matrix, a reactive framework from moi. So, yes, we can now program Flutter with a Lisp. Yay. Project includes dozens of working examples and a full implementation of the TodoMVC classic to help tire-kickers play around. Support installing freely available on the #matrix channel on the Clojurians Slack.

    2022 · github.com

  19. 19LC

    Complete llama.cpp tutorial for 2026. Install, compile with CUDA/Metal, run GGUF models, tune all inference flags, use the API server, speculative decoding, and benchmark your hardware. https://vucense.com/dev-corner/llama-cpp-tutorial-run-gguf-m...

    Apr 2026

  20. 20LA

    G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…

    2023 · github.com

  21. 21WM

    We wrote our inference engine on Rust, it is faster than llama cpp in all of the use cases. Your feedback is very welcomed. Written from scratch with idea that you can add support of any kernel and platform.

    2025 · github.com

  22. 22L3
  23. 23LA

    A simple mobile web app inspired by Fuzzy-Search/realtime-bakllava that uses llama.cpp server backend with multimodal mode to describe and narrate what the phone camera sees. I built this thing in a few hours using a single ChatGPT thread to generate most things for me and iterate on this project. Here's the workflow: https://chat.openai.com/share/ea84ec69-5617-45e8-8772-ac2dcf...

    2023 · github.com

  24. 24GA

    We’ve just launched Gradient — an API that helps you build private LLMs that you own. We simplify inference and fine-tuning on open-source LLMs such as llama2, and you only pay by the token. Our API platform makes it possible for you to create private models with a single API call. Run inference on your fine tuned model instantly with no cold boot (and no need to pay for compute costs). The product is truly on demand - when you run fine tuning and inference on our platform, there's nearly 0 startup latency for these API calls. And you're not paying for the compute, you just pay for the…

    2023 · gradient.ai

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