💥💥💥 Meta LLM Compiler, a family of models built on Meta Code Llama with additional code optimization and compiler capabilities. These models can emulate the compiler, predict optimal passes for code size, and disassemble code. They can be fine-tuned for new optimizations and compiler tasks. Hugging Face repo ➡️ go.fb.me/tdd3dw Research paper ➡️ go.fb.me/85zwgy LLM Compiler achieves state-of-the-art results on code size optimization and disassembly. This work shows that AI is learning to optimize code and can assist compiler experts in identifying opportunities to apply optimizations. LLM Compiler 7B & 13B models were released under a permissive license for both research and commercial use in the hopes of making it easier for developers and researchers alike to leverage this in their work and carry forward new research in this space. #machinelearning
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✨✨Meta AI has introduced the Meta Large Language Model Compiler (LLM Compiler), a suite of large language models designed for code optimization. These models, based on Code Llama, are trained on a substantial dataset of 546 billion tokens of LLVM-IR (an intermediate representation used in the LLVM compiler framework) and assembly code, available in 7 billion and 13 billion parameter sizes. ✨✨Key Features: 🤖 Training Data: 546 billion tokens of LLVM-IR and assembly code. 🤖 Fine-tuning Data: Additional 164 billion tokens for tasks like flag tuning and disassembly. 🤖 Context Size: Supports a 16k token context window. 🤖 Pretraining Focus: Specializes in LLVM-IR and assembly code. #AI #MachineLearning #CompilerOptimization #LLM #MetaAI #CodeOptimization
Today we’re releasing Meta LLM Compiler, a family of models built on Meta Code Llama with additional code optimization and compiler capabilities. The models achieve state-of-the-art results on optimization of code size and disassembly tasks. Hugging Face repo ➡️ https://go.fb.me/tdd3dw Research paper ➡️ https://go.fb.me/hvfnam LLM Compiler can emulate the compiler, predict optimal passes for code size, and disassemble code. It can be fine-tuned for new optimizations and compiler tasks. This work shows that AI is learning to optimize code and can assist compiler experts in identifying opportunities to apply optimizations. We believe this work could have an impact ranging from use in optimization for individual developer environments to inclusion in a compiler such as LLVM. We’re releasing LLM Compiler 7B & 13B models under a permissive license for both research and commercial use in the hopes of making it easier for developers and researchers alike to leverage this in their work and carry forward new research in this highly impactful space.
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#genAI: new offers in the open-source arena ▪️Meta has released Meta LLM Compiler. #LLMs are already widely used in software engineering for tasks such as ▪️generating code and documentation, ▪️translating code between programming languages, ▪️supporting testing and writing unit tests, and ▪️detecting and fixing bugs. In March 2024, researchers from Meta AI and Rice University introduced ▪️compiler optimization powered by LLMs with compiler feedback to optimize the code size of LLVM assembly. 📁 Article „Compiler generated feedback for Large Language Models“ on arXiv: https://lnkd.in/dJ3vzaBQ These developments facilitate that large open-source code datasets and Github-enabled models such as CodeLlama, ChatGPT, and Codex can help to develop a deeper understanding of various programming languages.
Today we’re releasing Meta LLM Compiler, a family of models built on Meta Code Llama with additional code optimization and compiler capabilities. The models achieve state-of-the-art results on optimization of code size and disassembly tasks. Hugging Face repo ➡️ https://go.fb.me/tdd3dw Research paper ➡️ https://go.fb.me/hvfnam LLM Compiler can emulate the compiler, predict optimal passes for code size, and disassemble code. It can be fine-tuned for new optimizations and compiler tasks. This work shows that AI is learning to optimize code and can assist compiler experts in identifying opportunities to apply optimizations. We believe this work could have an impact ranging from use in optimization for individual developer environments to inclusion in a compiler such as LLVM. We’re releasing LLM Compiler 7B & 13B models under a permissive license for both research and commercial use in the hopes of making it easier for developers and researchers alike to leverage this in their work and carry forward new research in this highly impactful space.
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Pretrained on over 500B tokens of LLVM-IR, x86_84, ARM, and CUDA assembly codes, this is a breakthrough in compiler design using LLMs! Can't wait to see its effect on Edge AI optimization for resource constrained devices!
Today we’re releasing Meta LLM Compiler, a family of models built on Meta Code Llama with additional code optimization and compiler capabilities. The models achieve state-of-the-art results on optimization of code size and disassembly tasks. Hugging Face repo ➡️ https://go.fb.me/tdd3dw Research paper ➡️ https://go.fb.me/hvfnam LLM Compiler can emulate the compiler, predict optimal passes for code size, and disassemble code. It can be fine-tuned for new optimizations and compiler tasks. This work shows that AI is learning to optimize code and can assist compiler experts in identifying opportunities to apply optimizations. We believe this work could have an impact ranging from use in optimization for individual developer environments to inclusion in a compiler such as LLVM. We’re releasing LLM Compiler 7B & 13B models under a permissive license for both research and commercial use in the hopes of making it easier for developers and researchers alike to leverage this in their work and carry forward new research in this highly impactful space.
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Here's why Meta LLM Compiler achieves state-of-the-art results in optimizing code size and disassembly tasks: 1. **Building on Code Llama:** Meta LLM Compiler takes the foundation of Code Llama, a large language model (LLM) specifically trained for code understanding. This provides a strong base for comprehending code structure and functionality. 2. **Enhanced Code Optimization and Compiler Reasoning:** The compiler goes beyond Code Llama's capabilities by being fine-tuned for tasks related to code optimization and understanding compiler actions. This specialization allows it to reason about the impact of optimizations and make informed suggestions. 3. **Focus on Intermediate Representations (IRs) and Assembly:** The model is trained on compiler intermediate representations (IRs) and assembly language. IRs are a format that compilers use internally to represent code, and assembly is a low-level language directly understandable by processors. By being familiar with these representations, the compiler can analyze code structure more effectively and identify optimization opportunities. 4. **Openly Available Pre-trained Models:** Meta provides a suite of pre-trained LLM Compiler models. These models are ready to use, allowing developers to leverage their capabilities without the need for extensive training from scratch. This accessibility fosters further research and development in code optimization. In summary, Meta LLM Compiler combines the strengths of Code Llama with additional training focused on compiler tasks and code representations. This specialization allows it to outperform previous models in optimizing code size and performing disassembly tasks.
Today we’re releasing Meta LLM Compiler, a family of models built on Meta Code Llama with additional code optimization and compiler capabilities. The models achieve state-of-the-art results on optimization of code size and disassembly tasks. Hugging Face repo ➡️ https://go.fb.me/tdd3dw Research paper ➡️ https://go.fb.me/hvfnam LLM Compiler can emulate the compiler, predict optimal passes for code size, and disassemble code. It can be fine-tuned for new optimizations and compiler tasks. This work shows that AI is learning to optimize code and can assist compiler experts in identifying opportunities to apply optimizations. We believe this work could have an impact ranging from use in optimization for individual developer environments to inclusion in a compiler such as LLVM. We’re releasing LLM Compiler 7B & 13B models under a permissive license for both research and commercial use in the hopes of making it easier for developers and researchers alike to leverage this in their work and carry forward new research in this highly impactful space.
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Need to review(llvm)
Today we’re releasing Meta LLM Compiler, a family of models built on Meta Code Llama with additional code optimization and compiler capabilities. The models achieve state-of-the-art results on optimization of code size and disassembly tasks. Hugging Face repo ➡️ https://go.fb.me/tdd3dw Research paper ➡️ https://go.fb.me/hvfnam LLM Compiler can emulate the compiler, predict optimal passes for code size, and disassemble code. It can be fine-tuned for new optimizations and compiler tasks. This work shows that AI is learning to optimize code and can assist compiler experts in identifying opportunities to apply optimizations. We believe this work could have an impact ranging from use in optimization for individual developer environments to inclusion in a compiler such as LLVM. We’re releasing LLM Compiler 7B & 13B models under a permissive license for both research and commercial use in the hopes of making it easier for developers and researchers alike to leverage this in their work and carry forward new research in this highly impactful space.
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More and more interest around LLM trained around advanced coding funcionalities... Cit. "There is increasing interest in large language models (LLMs) for software engineering tasks including code generation, code translation, and code testing"
Today we’re releasing Meta LLM Compiler, a family of models built on Meta Code Llama with additional code optimization and compiler capabilities. The models achieve state-of-the-art results on optimization of code size and disassembly tasks. Hugging Face repo ➡️ https://go.fb.me/tdd3dw Research paper ➡️ https://go.fb.me/hvfnam LLM Compiler can emulate the compiler, predict optimal passes for code size, and disassemble code. It can be fine-tuned for new optimizations and compiler tasks. This work shows that AI is learning to optimize code and can assist compiler experts in identifying opportunities to apply optimizations. We believe this work could have an impact ranging from use in optimization for individual developer environments to inclusion in a compiler such as LLVM. We’re releasing LLM Compiler 7B & 13B models under a permissive license for both research and commercial use in the hopes of making it easier for developers and researchers alike to leverage this in their work and carry forward new research in this highly impactful space.
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Today we’re releasing Meta LLM Compiler, a family of models built on Meta Code Llama with additional code optimization and compiler capabilities. The models achieve state-of-the-art results on optimization of code size and disassembly tasks. Hugging Face repo ➡️ https://go.fb.me/tdd3dw Research paper ➡️ https://go.fb.me/hvfnam LLM Compiler can emulate the compiler, predict optimal passes for code size, and disassemble code. It can be fine-tuned for new optimizations and compiler tasks. This work shows that AI is learning to optimize code and can assist compiler experts in identifying opportunities to apply optimizations. We believe this work could have an impact ranging from use in optimization for individual developer environments to inclusion in a compiler such as LLVM. We’re releasing LLM Compiler 7B & 13B models under a permissive license for both research and commercial use in the hopes of making it easier for developers and researchers alike to leverage this in their work and carry forward new research in this highly impactful space.
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Now this is exciting news! It seems every day a new or improved LLM model is announced. Each one with slightly improved characteristics, but mostly, at least from my perspective, of scientific interest. This however opens up quite some new use cases.💪 Working on development tools in the past myself, I'm curious to see how this will be productized eventually. #GenAI #AI
Today we’re releasing Meta LLM Compiler, a family of models built on Meta Code Llama with additional code optimization and compiler capabilities. The models achieve state-of-the-art results on optimization of code size and disassembly tasks. Hugging Face repo ➡️ https://go.fb.me/tdd3dw Research paper ➡️ https://go.fb.me/hvfnam LLM Compiler can emulate the compiler, predict optimal passes for code size, and disassemble code. It can be fine-tuned for new optimizations and compiler tasks. This work shows that AI is learning to optimize code and can assist compiler experts in identifying opportunities to apply optimizations. We believe this work could have an impact ranging from use in optimization for individual developer environments to inclusion in a compiler such as LLVM. We’re releasing LLM Compiler 7B & 13B models under a permissive license for both research and commercial use in the hopes of making it easier for developers and researchers alike to leverage this in their work and carry forward new research in this highly impactful space.
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Executive Leader | Technology & Products Innovation AI | Product Strategy | AI Expertise
Meta LLM Compiler: Foundation Models for Code Compiler Optimization
Today we’re releasing Meta LLM Compiler, a family of models built on Meta Code Llama with additional code optimization and compiler capabilities. The models achieve state-of-the-art results on optimization of code size and disassembly tasks. Hugging Face repo ➡️ https://go.fb.me/tdd3dw Research paper ➡️ https://go.fb.me/hvfnam LLM Compiler can emulate the compiler, predict optimal passes for code size, and disassemble code. It can be fine-tuned for new optimizations and compiler tasks. This work shows that AI is learning to optimize code and can assist compiler experts in identifying opportunities to apply optimizations. We believe this work could have an impact ranging from use in optimization for individual developer environments to inclusion in a compiler such as LLVM. We’re releasing LLM Compiler 7B & 13B models under a permissive license for both research and commercial use in the hopes of making it easier for developers and researchers alike to leverage this in their work and carry forward new research in this highly impactful space.
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Meta introduced "LLM Compiler", focused on code optimization 💡 LLM Compiler is a suite of robust, openly available, pre-trained models. Leveraging 546b tokens of LLVM-IR and assembly code, it is built on Code Llama and is designed to enhance the understanding and optimization of compiler intermediate representations and assembly language 🛠️ Available in 7b and 13b parameter models, the LLM Compiler achieves 77% of the optimizing potential of autotuning and 45% accuracy in disassembling x86_64 and ARM assembly back to LLVM-IR 💻 Meta LLM Compiler will be available under a bespoke commercial license to allow wide reuse. #AI #MachineLearning #DataScience #CompilerOptimization #TechInnovation #TechNews
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