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Check out mistral.​rs, our #Rust-based open source inference engine allowing for fast #LLM serving for a variety of architectures including X-LoRA mixture-of-expert (MoE) models, Llama-3, Mistral/Mixtral, Gemma & many others. Built on the Hugging Face #Candle framework for #Rust w/ custom CUDA kernels in the backend (as well as...

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Markus J. Buehler

20,454 subscribers

73,575 görüntüleme • 2 yıl önce •via X (Twitter)

EğitimBilim & Teknoloji#Rust#LLM#Candle#Rust
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nicoarq profil fotoğrafı
nicoarq2 yıl önce

@huggingface This is really rly cool! I thought it was only limited to Mistral related LLMs though maybe it's not too late to change the name to something generic to not confuse people?

Markus J. Buehler profil fotoğrafı
Markus J. Buehler2 yıl önce

@huggingface Yes, the tool with with many architectures, including Llama-3, Phi-3 (up to 128k context), Mistral/Mixtral, Gemma, X-LoRA mixture-of-expert (MoE) models, & many others. Also features in-situ quantization to any level.

Ingo Villnow (DM5DK) 🇺🇦🌻 profil fotoğrafı
Ingo Villnow (DM5DK) 🇺🇦🌻2 yıl önce

@huggingface Awesome! More apps like this written in Rust 😍

Jonathan Eisenzopf profil fotoğrafı
Jonathan Eisenzopf2 yıl önce

@huggingface This looks really cool. I’ve been trying to figure out optimal branching in rust candle. Nice job.

Thomas Wolf profil fotoğrafı
Thomas Wolf2 yıl önce

@huggingface wow!

PΔBLØ ᄃΞ profil fotoğrafı
PΔBLØ ᄃΞ2 yıl önce

@huggingface 🦀

Alexander Ocsa profil fotoğrafı
Alexander Ocsa2 yıl önce

@huggingface Does it support GPU hardware acceleration ?

Nicolas Patry profil fotoğrafı
Nicolas Patry2 yıl önce

@huggingface Impressive work !

Markus J. Buehler profil fotoğrafı
Markus J. Buehler2 yıl önce

@huggingface Thank you!

iandanforth 🦋 @iandanforth.bsky.social profil fotoğrafı
iandanforth 🦋 @iandanforth.bsky.social2 yıl önce

@_philschmid @huggingface Is this affiliated with Mistral AI? The name certainly implies it.

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I trained a 12M parameter LLM on my own ML framework using a Rust backend and CUDA kernels for flash attention, AdamW, and more. Wrote the full transformer architecture, and BPE tokenizer from scratch. The framework features: - Custom CUDA kernels (Flash Attention, fused LayerNorm, fused GELU) for 3x increased throughput - Automatic WebGPU fallback for non-NVIDIA devices - TypeScript API with Rust compute backend - One npm install to get started, prebuilt binaries for every platform Try out the model for yourself: Built with Reese Chong. Check out the repos and blog if you want to learn more. Shoutout to Modal for the compute credits allowing me to train on 2 A100 GPUs without going broke cc sunny madra Gavin
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I trained a 12M parameter LLM on my own ML framework using a Rust backend and CUDA kernels for flash attention, AdamW, and more. Wrote the full transformer architecture, and BPE tokenizer from scratch. The framework features: - Custom CUDA kernels (Flash Attention, fused LayerNorm, fused GELU) for 3x increased throughput - Automatic WebGPU fallback for non-NVIDIA devices - TypeScript API with Rust compute backend - One npm install to get started, prebuilt binaries for every platform Try out the model for yourself: Built with Reese Chong. Check out the repos and blog if you want to learn more. Shoutout to Modal for the compute credits allowing me to train on 2 A100 GPUs without going broke cc sunny madra Gavin

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