burn VS candle

Compare burn vs candle and see what are their differences.

burn

Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. (by tracel-ai)

candle

Minimalist ML framework for Rust (by huggingface)
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burn candle
9 18
7,581 14,168
6.7% 4.9%
9.8 9.9
6 days ago 2 days ago
Rust Rust
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

burn

Posts with mentions or reviews of burn. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-26.

candle

Posts with mentions or reviews of candle. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-06-04.
  • Vector search in Manticore
    7 projects | dev.to | 4 Jun 2024
    While looking into how to create text embeddings quickly and directly, we discovered a few helpful tools that allowed us to achieve our goal. Consequently, we created an easy-to-use PHP extension that can generate text embeddings. This extension lets you pick any model from Sentence Transformers on HuggingFace. It is built on the CandleML framework, which is written in Rust and is a part of the well-known HuggingFace ecosystem. The PHP extension itself is also crafted in Rust using the php-ext-rs library. This approach ensures the extension runs fast while still being easy to develop.
  • karpathy/llm.c
    10 projects | news.ycombinator.com | 8 Apr 2024
    Candle already exists[1], and it runs pretty well. Can use both CUDA and Metal backends (or just plain-old CPU).

    [1] https://github.com/huggingface/candle

  • Best alternative for python
    2 projects | /r/deeplearning | 6 Dec 2023
  • Is there any LLM that can be installed with out python
    2 projects | /r/LocalLLaMA | 5 Dec 2023
    Check out Candle! It's a Deep Learning framework for Rust. You can run LLMs in binaries.
  • Announcing Kalosm - an local first AI meta-framework for Rust
    2 projects | /r/rust | 12 Nov 2023
    Kalosm is a meta-framework for AI written in Rust using candle. Kalosm supports local quantized large language models like Llama, Mistral, Phi-1.5, and Zephyr. It also supports other quantized models like Wuerstchen, Segment Anything, and Whisper. In addition to local models, Kalosm supports remote models like GPT-4 and ada embeddings.
  • RFC: candle-lora
    2 projects | /r/rust | 24 Oct 2023
    I have been working on a machine learning library called candle-lora for Candle. It implementes a technique called LoRA (low rank adaptation), which allows you to reduce a model's trainable parameter count by wrapping and freezing old layers.
  • ExecuTorch: Enabling On-Device interference for embedded devices
    4 projects | news.ycombinator.com | 17 Oct 2023
    [2] https://github.com/huggingface/candle/issues/313
  • [P] Open-source project to run locally LLMs in browser, such as Phi-1.5 for fully private inference
    2 projects | /r/MachineLearning | 6 Oct 2023
    We provide full local inference in browser, by using libraries from Hugging Face like transformers.js or candle for WASM inference.
  • Update on the Candle ML framework.
    1 project | /r/rust | 27 Sep 2023
    We've first announced Candle, a minimalist ML framework in Rust 6 weeks ago. Since then we've focused on adding various recent models and improved the framework so as to support the necessary features in an efficient way. You can checkout a gallery of the examples, supported models include:
  • Should I Haskell or OCaml?
    4 projects | news.ycombinator.com | 16 Sep 2023
    How did you select those two as your options?

    I'm just a hobbyist that enjoys programming, and I eventually wanted to expand beyond python. I looked at Haskell and read Learn You a Haskell and did some Exercism exercises but never got anywhere close to being able to use it for real projects. Have been trying to learn about Lisp lately and feel like I've come to a similar dead end.

    On the other hand, both Go and Rust have felt fulfilling and practical, with static typing and solid tooling, cross compilations, static binaries, and dependency management that is just a huge breath of fresh air coming from python.

    The ML / data science scene is nowhere near as developed as in Python, and I still lean on jupyter/polars/PyTorch here, but I think the candle project[0] seems very interesting. Compiling whisper down to a single CUDA-leveraging binary for fast local transcription is pretty cool!

    [0]: https://github.com/huggingface/candle

What are some alternatives?

When comparing burn and candle you can also consider the following projects:

dfdx - Deep learning in Rust, with shape checked tensors and neural networks

Universal-G-Code-Sender - A cross-platform G-Code sender for GRBL, Smoothieware, TinyG and G2core.

wonnx - A WebGPU-accelerated ONNX inference run-time written 100% in Rust, ready for native and the web

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]

tch-rs - Rust bindings for the C++ api of PyTorch.

rust-mlops-template - A work in progress to build out solutions in Rust for MLOPs

bCNC - GRBL CNC command sender, autoleveler and g-code editor

llama2.rs - A fast llama2 decoder in pure Rust.

gsender - Connect to and control Grbl-based CNCs with ease

albumin - Simple Hierarchical Album Generator

cncjs - A web-based interface for CNC milling controller running Grbl, Marlin, Smoothieware, or TinyG.

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