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Overview
PyTorch is the Deep Learning stack that has achieved the greatest popularity in research and industry.
A broad and consolidated ecosystem has developed around it for each application domain (Computer Vision, Natural Language Processing, Graph Neural Networks, Diffusion Models etc.).
Quantyca has confirmed in its projects a profound expertise in PyTorch and the surrounding frameworks, such as fast.ai, HuggingFace, Detectron and Timm.
Building on the core components of PyTorch, developed by Meta, a series of frameworks have emerged over time that address different application modes:
  • Timm and Detectron for Computer Vision (Classification, Detection, Segmentation etc.)
  • HuggingFace for NLP (Text Analysis, Entity Extraction, Semantic Search)
  • fast.ai as a meta-framework for prototyping, training and deployment

These libraries have two goals:

  • Create high-level APIs to make it easy to design and deploy solutions
  • Offer a catalogue of semi-processed models to enable fine-tuning on proprietary customer datasets

Quantyca's vision

Quantyca helps its customers create PyTorch-based solutions, supporting them at every stage of design, deployment and production support.
Distinctive technological competences are:

  • Efficient and structured fine-tuning approach to make the most of datasets
  • Integration into cloud infrastructure
  • Creation of inference APIs on cloud and on-edge

Use Cases

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