PyTorch
Meta's flexible deep learning framework, favored for research and rapid model experimentation.
Discuss your projectPyTorch's dynamic computation graph and Pythonic API make it our preferred tool for prototyping and fine-tuning custom deep learning models — it's the framework most modern research and open-source models are published in first.
We use PyTorch when a project needs a fine-tuned or custom-trained model rather than an off-the-shelf API, including fine-tuning open-source LLMs for a client's specific domain.
How we use PyTorch
Model fine-tuning
Fine-tuning open-source models on a client's own data for a specific task or domain.
Research-grade prototyping
Fast experimentation on novel model architectures before productionizing.
Custom deep learning
Bespoke neural network models for problems generic APIs can't solve.
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