The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
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The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Translated"Lee Hung-yi's Deep Learning Tutorial" (recommended by Professor Hung-yi Lee 👍, the Apple Book 🍎), PDF download address: https://github.com/datawhalechina/leedl-tutorial/releases
- machine-learning
- deep-learning
- leedl-tutorial
- cnn
Bringing stable diffusion models to web browsers. Everything runs inside the browser with no server support.
- webgpu
- deep-learning
- stable-diffusion
- web-assembly
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
- data-science
- python
- dag
- data-engineering
Wrapper for RDKit's RunReactants to improve stereochemistry handling
Breaking captchas using torch
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
- tensorflow-2
- tensorflow-lite
- on-device-ml
- model-quantization
Compilado de recursos sobre Computação Quântica em português
Big Data essentials: Hadoop, MapReduce, Spark. Explore tutorials and demos in Jupyter notebooks—most are self-contained and live, ready to run with a click.
a nose plugin for finding and running IPython notebooks as nose tests