candle
learn-you-a-haskell
candle | learn-you-a-haskell | |
---|---|---|
17 | 77 | |
13,475 | 294 | |
4.4% | - | |
9.9 | 0.0 | |
4 days ago | over 1 year ago | |
Rust | Makefile | |
Apache License 2.0 | - |
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.
candle
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karpathy/llm.c
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
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Is there any LLM that can be installed with out python
Check out Candle! It's a Deep Learning framework for Rust. You can run LLMs in binaries.
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Announcing Kalosm - an local first AI meta-framework for Rust
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.
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RFC: candle-lora
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.
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ExecuTorch: Enabling On-Device interference for embedded devices
[2] https://github.com/huggingface/candle/issues/313
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[P] Open-source project to run locally LLMs in browser, such as Phi-1.5 for fully private inference
We provide full local inference in browser, by using libraries from Hugging Face like transformers.js or candle for WASM inference.
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Update on the Candle ML framework.
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:
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Should I Haskell or OCaml?
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
- Minimalist ML framework for Rust
learn-you-a-haskell
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Revisiting Haskell after 10 years
The LYAH is by far my favorite book for beginners, however, it lacks exercises for you to practice, but you can still move along typing and playing with the examples shown, and it’s free to read online. It’s outdated but most of the code may still be valid with little to no changes.
- [2023 Day 09] How today felt
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Should I Haskell or OCaml?
Learn You a Haskell For Great Good! is also a really good resource:
https://learnyouahaskell.com/
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How late is too late to change tech stacks?
If you've never done functional, Learn You Some Erlang For Great Good was a very fun read, and I'll always love Learn You a Haskell for Great Good for showing me everything imperative languages kinda gloss over magically, as well as why I should never take a job working in Haskell!
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So Hows the Hackathon Going?
you start that way, but don't do http://learnyouahaskell.com really?
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I want to learn fn programming
Learn You a Haskell for Great Good!
- help i just discovered haskell 38 hours ago and i think i love it
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Haskell book after Get Programming with Haskell?
I enjoyed http://learnyouahaskell.com/ which is available in print and digital. Fun and lighthearted while still teaching reasonable depth. YMMV.
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Why I decided to learn (and teach) Clojure
Elm is a statically typed language inspired by Haskell. The natural step would be to use Elm on the frontend and Haskell on the backend. And that's what I tried to do. I read with some difficulty the Learn You a Haskell for Great Good! book (available for free here) and learned a lot of cool stuff. But creating a complete backend using Haskell proved to be more than I could chew. So I decided to look for alternatives...
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I’m trying coding
Here y’go!
What are some alternatives?
Universal-G-Code-Sender - A cross-platform G-Code sender for GRBL, Smoothieware, TinyG and G2core.
learn4haskell - 👩🏫 👨🏫 Learn Haskell basics in 4 pull requests
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]
plutus-pioneer-program - This repository hosts the lectures of the Plutus Pioneers Program. This program is a training course that the IOG Education Team provides to recruit and train software developers in Plutus, the native smart contract language for the Cardano ecosystem.
tch-rs - Rust bindings for the C++ api of PyTorch.
learn-you-a-haskell-notebook - Jupyter adaptation of Learn You a Haskell for Great Good!
bCNC - GRBL CNC command sender, autoleveler and g-code editor
coq - Coq is a formal proof management system. It provides a formal language to write mathematical definitions, executable algorithms and theorems together with an environment for semi-interactive development of machine-checked proofs.
gsender - Connect to and control Grbl-based CNCs with ease
algebra-driven-design - Source material for Algebra-Driven Design
cncjs - A web-based interface for CNC milling controller running Grbl, Marlin, Smoothieware, or TinyG.
integrant - Micro-framework for data-driven architecture