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Ilyas Moutawwakil
IlyasMoutawwakil
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IlyasMoutawwakil
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Optimization, LLMs, Hardware, Backends, ..
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🚀 Optimum: The Last v1 Release 🚀 Optimum v1.27 marks the final major release in the v1 series. As we close this chapter, we're laying the groundwork for a more modular and community-driven future: - Optimum v2: A lightweight core package for porting Transformers, Diffusers, or Sentence-Transformers to specialized AI hardware/software/accelerators.. - Optimum‑ONNX: A dedicated package where the ONNX/ONNX Runtime ecosystem lives and evolves, faster-moving and decoupled from the Optimum core. 🎯 Why this matters: - A clearer governance path for ONNX, fostering stronger community collaboration and improved developer experience.. - Enable innovation at a faster pace in a more modular, open-source environment. 💡 What this means: - More transparency, broader participation, and faster development driven by the community and key actors in the ONNX ecosystem (PyTorch, Microsoft, Joshua Lochner 👀, ...) - A cleaner, more maintainable core Optimum, focused on extending HF libraries to special AI hardware/software/accelerators tooling and used by our partners (Intel Corporation, Amazon Web Services (AWS), AMD, NVIDIA, FuriosaAI, ...) 🛠️ Major updates I worked on in this release: ✅ Added support for Transformers v4.53 and SmolLM3 in ONNX/ONNXRuntime. ✅ Solved batched inference/generation for all supported decoder model architectures (LLMs). ✨ Big shoutout to @echarlaix for leading the refactoring work that cleanly separated ONNX exporter logic and enabled the creation of Optimum‑ONNX. 📝 Release Notes: https://lnkd.in/gXtE_qji 📦 Optimum : https://lnkd.in/ecAezNT6 🎁 Optimum-ONNX: https://lnkd.in/gzjyAjSi #Optimum #ONNX #OpenSource #HuggingFace #Transformers #Diffusers
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Introducing AutoRound: Intel’s Advanced Quantization for LLMs and VLMs
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IlyasMoutawwakil/benchmarks
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IlyasMoutawwakil/OpenVINO-Benchmarks
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IlyasMoutawwakil/optimum-benchmarks-ci
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IlyasMoutawwakil/llm-race-dataset
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