fastai/timmdocs
Documentation for Ross Wightman's timm image model library
This documentation helps machine learning engineers and researchers quickly find and use state-of-the-art image recognition models. It provides clear instructions for selecting from over 300 models, loading them (optionally with pre-trained weights), and customizing them for specific image classification tasks. You input the name of a model, and it outputs a ready-to-use model for integrating into your deep learning workflows.
320 stars. No commits in the last 6 months.
Use this if you need to rapidly prototype or deploy high-performance image classification models for tasks like object recognition, content moderation, or medical image analysis.
Not ideal if you are looking for guidance on building image models from scratch or need detailed theoretical explanations of model architectures.
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Jupyter Notebook
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Apache-2.0
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Last pushed
Apr 17, 2024
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