Patrick Von Platen
Research Engineer at Mistral AI
France
Summary
🤩
Rockstar🎓
Top SchoolPatrick Von Platen is a research engineer with nine years of experience building and maintaining open-source ML tooling, currently at Mistral AI after a senior technical lead tenure at Hugging Face. He led and created the widely used Diffusers library and has been a core maintainer of Transformers, contributing production-grade generation, diffusion, and audio model support that powers thousands of daily installs. His hands-on contributions span safety checkers for image generation, audio feature engineering, high-throughput LLM inference (vLLM), and integrating LoRA and vision-language adapters for Mistral inference. Patrick combines deep research training (PhD-level work at Cambridge and speech research at RWTH) with pragmatic backend engineering to optimize performance, testing, and model loading across PyTorch/Flax ecosystems. He is notable for improving evaluation metrics and large-model loading tooling (accelerate, safetensors) and for moving state-of-the-art audio models like Wav2Vec2 into mainstream use. Based in France, he blends academic rigor with production-focused open-source impact across Transformers, Diffusers, and related ML infrastructure.
9 years of coding experience
3 years of employment as a software developer
Engineer’s Degree Engineering, Engineer’s Degree Engineering at CentraleSupélecDoctor of Philosophy - PhD Computer Engineering, Doctor of Philosophy - PhD Computer Engineering at University of CambridgeMaster of Science - MS Computer Engineering, Master of Science - MS Computer Engineering at RWTH Aachen University
English, French, German, Spanish
Stackoverflow
82reputation
2kreached
4answers
2questions
Github Skills (59)
transformers10
git10
pytorch10
distributed-training10
python10
evaluation10
image-processing10
testing10
diffusion-models10
machine-learning10
audio-processing10
stable-diffusion10
model-management10
inference10
encoder-decoder10
Programming languages (10)
Github contributions (5)
mistralai/mistral-inference
May 2024 - Mar 2025
Official inference library for Mistral models
Role in this project:
ML Engineer
ML EngineerContributions:4 releases, 21 reviews, 35 PRs in 10 months
Contributions summary:Patrick primarily contributed to the `mistral-inference` repository, which focuses on inference for Mistral models. Their contributions involved significant code changes within the core inference library, including modifications to model architecture, attention mechanisms, and the integration of LoRA (Low-Rank Adaptation) for model fine-tuning. The user also added code related to vision-language adapters and pipeline parallelism, indicating involvement in optimizing inference and expanding model capabilities. These changes suggest a focus on improving the performance, features, and adaptability of the Mistral models for various inference tasks.
llmllm-inferencemistralai
huggingface/diffusers
May 2022 - Jan 2023
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
Role in this project:Backend Developer & Machine Learning Engineer
Backend Developer & Machine Learning EngineerContributions:36 releases, 5419 reviews, 752 commits in 8 months
Contributions summary:Patrick's contributions primarily focus on implementing and documenting changes related to the Latent Diffusion model. Their work included adding pipeline documentation, logging improvements, and enhancing the stability of the inference steps. They also focused on applying attention slicing and adding inpainting capabilities to improve the model's performance.
pytorchartdeep-learningimage2imagestate-of-the-art
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