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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.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
A game theoretic approach to explain the output of any machine learning model.
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
A collection of various deep learning architectures, models, and tips
A multi-voice TTS system trained with an emphasis on quality
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Tacotron 2 - PyTorch implementation with faster-than-realtime inference
Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest research
Segment Anything in High Quality [NeurIPS 2023]
A modern Anki custom scheduling based on Free Spaced Repetition Scheduler algorithm
Fast and flexible AutoML with learning guarantees.
A small package to create visualizations of PyTorch execution graphs
Beaker Extensions for Jupyter Notebook
Benchmarking large language models' complex reasoning ability with chain-of-thought prompting
Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads
🎁 6,500,000+ Unsplash images made available for research and machine learning
[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.
A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
Datasets, tools, and benchmarks for representation learning of code.
Beyond Accuracy: Behavioral Testing of NLP models with CheckList
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Training PyTorch models with differential privacy
Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).
Demo of running NNs across different frameworks