smolrsrwkv
A relatively basic implementation of RWKV in Rust written by someone with very little math and ML knowledge. Supports 32, 8 and 4 bit evaluation. It can also directly load PyTorch RWKV models. (by KerfuffleV2)
neuronika
Tensors and dynamic neural networks in pure Rust. (by neuronika)
smolrsrwkv | neuronika | |
---|---|---|
6 | 19 | |
91 | 1,033 | |
- | 1.3% | |
5.6 | 0.0 | |
8 months ago | over 1 year ago | |
Rust | Rust | |
MIT License | 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.
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.
smolrsrwkv
Posts with mentions or reviews of smolrsrwkv.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-06.
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Introducing repugnant-pickle, a crate for scraping Python Pickle files in a basic way. Notable, it can deal with (some) PyTorch model files.
For an example of actually using it, you can look at my little project for running inference on RWKV models: https://github.com/KerfuffleV2/smolrsrwkv It uses repugnant-pickle to enable loading PyTorch models directly with no conversion requirement or Python dependencies.
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Is GPT-4 still just a language model trying to predict text?
If you want some proof, I wrote my own application that can run inference on RWKV models (competing approach similar to GPT which most LLMs use currently): https://github.com/KerfuffleV2/smolrsrwkv
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I created a simple implementation of the RWKV language model (RWKV competes with the dominant Transformers-based approach which is the "T" in GPT)
It can now quantize to 8bit for 4x memory savings: https://github.com/KerfuffleV2/smolrsrwkv/tree/experiment-quantize
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ChatGPT saved this dog's life...
Here's an implementation of RWKV I wrote that can run inference on models: https://github.com/KerfuffleV2/smolrsrwkv
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LLMs are not that different from us -- A delve into our own conscious process
Now, I'm not an expert but I do know a little more than the average person. I actually just got done implementing a simple one based on the RWKV approach rather than transformers: https://github.com/KerfuffleV2/smolrsrwkv
neuronika
Posts with mentions or reviews of neuronika.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-02.
- This year I tried solving AoC using Rust, here are my impressions coming from Python!
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Deep Learning in Rust: Burn 0.4.0 released and plans for 2023
Also perhaps comparing to Neuronika.
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Making a better Tensorflow thanks to strong typing
how does it compare with https://github.com/spearow/juice, https://github.com/neuronika/neuronika and https://github.com/spearow/juice?
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[D] To what extent can Rust be used for Machine Learning?
Check where and how this struct is used. https://github.com/neuronika/neuronika/blob/variable-rework/neuronika-variable/src/history.rs
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What do I need for an ML/DL based scripting language in Rust?
Also you can take a look at neuronika.
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ML in Rust
There is also https://github.com/neuronika/neuronika
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Enzyme: Towards state-of-the-art AutoDiff in Rust
I have a question: as the maintainer of [neuronika](https://github.com/neuronika/neuronika), a crate that offers dynamic neural network and auto-differentiation with dynamic graphs, I'm looking at a future possible feature for such framework consisting in the possibility of compiling models, getting thus rid of the "dynamic" part, which is not always needed. This would speed the inference and training times quite a bit.
- Any role that Rust could have in the Data world (Big Data, Data Science, Machine learning, etc.)?
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What sort of mature, open-source libraries do you feel Rust should have but currently lacks?
If you like autograd you will love neuronika
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bhtsne 0.5.0, now 5.6x faster on a 4 core machine, plus a summary of my Rust journey (so far)
After reading most of the book, I wanted to get my hands dirty. My initial idea was to build a small machine learning framework but I deemed it to be too difficult if not impossible for me at the time. (Now, neuronika would have something to say). When gathering the bibliography for my thesis, I recalled to have stumbled upon a particular algorithm, t-SNE, whom I liked very much. I found the idea behind it to be very clever and elegant (t-SNE it's still one of my favorite algorithms, together with backprop and SOM, I find manifold learning fascinating in general). "So be it", I said, and I began writing a mess of a code, that was basically a translation of the C++ implementation. Boy was it bad.