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SaaSHub
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better tch-rs alternative or higher similarity.
tch-rs reviews and mentions
Posts with mentions or reviews of tch-rs.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-08-05.
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Llama2.rs: One-file Rust implementation of Llama2
I wanted to do something like this but then I would miss on proper CUDA acceleration and lose performance compared to using torchlib.
I wrote a forgettable llama implementation for https://github.com/LaurentMazare/tch-rs (pytorch's torchlib rust binding).
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Playing Atari Games in OCaml
I first encountered OCaml's PyTorch bindings because apparently they generate a C wrapper around PyTorch's C++ API, and Rust's PyTorch bindings use OCaml's C wrapper. See: https://github.com/LaurentMazare/tch-rs
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llm: a Rust crate/CLI for CPU inference of LLMs, including LLaMA, GPT-NeoX, GPT-J and more
You could try looking at the min-GPT example of tch-rs. I'd also strongly suggest watching Karpathy's video to understand what's going on.
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A Rust client library for interacting with Microsoft Airsim https://github.com/Sollimann/airsim-client
Pytorch
- [D] HuggingFace in Julia or Rust ?
- This year I tried solving AoC using Rust, here are my impressions coming from Python!
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[Help Needed] Deployment of torchscript using rust
I have looked into this a bit and found some crates which help in loading torchscript models called tch-rs
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Stable Diffusion with Core ML on Apple Silicon
PyTorch has libtorch as its purely native library. There are also Rust bindings for libtorch:
https://github.com/LaurentMazare/tch-rs
I used this in the past to make a transformer-based syntax annotator. Fully in Rust, no Python required:
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I could use some basic help
The game is in Rust, and so I have been working at using the pytorch Rust bindings, which have an A2C example, so that's what I've been going with. Example here: https://github.com/LaurentMazare/tch-rs/blob/main/examples/reinforcement-learning/a2c.rs
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Announcing Burn: New Deep Learning framework with CPU & GPU support using the newly stabilized GAT feature
Burn is different: it is built around the Backend trait which encapsulates tensor primitives. Even the reverse mode automatic differentiation is just a backend that wraps another one using the decorator pattern. The goal is to make it very easy to create optimized backends and support different devices and use cases. For now, there are only 3 backends: NdArray (https://github.com/rust-ndarray/ndarray) for a pure rust solution, Tch (https://github.com/LaurentMazare/tch-rs) for an easy access to CUDA and cuDNN optimized operations and the ADBackendDecorator making any backend differentiable. I am now refactoring the internal backend API to make it as easy as possible to plug in new ones.
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A note from our sponsor - WorkOS
workos.com | 16 Apr 2024
Stats
Basic tch-rs repo stats
37
3,800
7.7
about 1 month ago
LaurentMazare/tch-rs is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of tch-rs is Rust.
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