Search Results for "model train design"
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Showing 5 open source projects for "model train design"
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1
Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
...It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior network is needed after all. And so research continues. For simpler training, you can directly supply text strings instead of precomputing text encodings. ... -
2
PyG
Graph Neural Network Library for PyTorch
...All it takes is 10-20 lines of code to get started with training a GNN model (see the next section for a quick tour). -
3
BerserkArch
A bleeding-edge, security-centric Arch-based Linux distribution.
BerserkArch is a security-focused, performance-tuned Linux operating system (OS) based on Arch Linux, designed for developers, hackers, and technical users. A bleeding-edge, security-centric Arch-based Linux distribution crafted for hackers, developers, and nerds alike. Following the Arch Linux philosophy, it is designed to be highly customizable, allowing users to build their environment with only the components they need, rather than having a lot of pre-installed software like some other... -
4
DeepCluster
Deep Clustering for Unsupervised Learning of Visual Features
DeepCluster is a classic self-supervised clustering-based representation learning algorithm that iteratively groups image features and uses the cluster assignments as pseudo-labels to train the network. In each round, features produced by the network are clustered (e.g. k-means), and the cluster IDs become supervision targets in the next epoch, encouraging the model to refine its representation to better separate semantic groups. This alternating “cluster & train” scheme helps the model gradually discover meaningful structure without labels. ... -
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5
Age and Gender Estimation
Keras implementation of a CNN network for age and gender estimation
Keras implementation of a CNN network for age and gender estimation. This is a Keras implementation of a CNN for estimating age and gender from a face image [1, 2]. In training, the IMDB-WIKI dataset is used. Because the face images in the UTKFace dataset is tightly cropped (there is no margin around the face region), faces should also be cropped in demo.py if weights trained by the UTKFace dataset is used. Please set the margin argument to 0 for tight cropping. You can evaluate a trained...
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