Best Engineering Software for Hugging Face
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Compare the Top Engineering Software that integrates with Hugging Face as of October 2025
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This a list of Engineering software that integrates with Hugging Face. Use the filters on the left to add additional filters for products that have integrations with Hugging Face. View the products that work with Hugging Face in the table below.
What is Engineering Software for Hugging Face?
Engineering software is software used by engineers to design, analyze and manufacture various products. It includes a wide range of applications such as CAD/CAE software, analysis tools, optimization tools, and programming tools. Engineering software can be used for a variety of tasks such as designing mechanical parts, analyzing structural stability, simulating system performance, and optimizing product designs. These applications enable engineers to optimize their designs for cost reduction and increased efficiency. Compare and read user reviews of the best Engineering software for Hugging Face currently available using the table below. This list is updated regularly.
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Evo 2
Arc Institute
Evo 2 is a genomic foundation model capable of generalist prediction and design tasks across DNA, RNA, and proteins. It utilizes a frontier deep learning architecture to model biological sequences at single-nucleotide resolution, achieving near-linear scaling of compute and memory relative to context length. Trained with 40 billion parameters and a 1 megabase context length, Evo 2 processes over 9 trillion nucleotides from diverse eukaryotic and prokaryotic genomes. This extensive training enables Evo 2 to perform zero-shot function prediction across multiple biological modalities, including DNA, RNA, and proteins, and to generate novel sequences with plausible genomic architecture. The model's capabilities have been demonstrated in tasks such as designing functional CRISPR systems and predicting disease-causing mutations in human genes. Evo 2 is publicly accessible via Arc's GitHub repository and is integrated into the NVIDIA BioNeMo framework.
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