Host Git-based models, datasets and Spaces on the BOINCAI Hub.
BOINC AI Hub documentation.
State-of-the-art ML for Pytorch, TensorFlow, and JAX.
Access and share datasets for computer vision, audio, and NLP tasks.
State-of-the-art diffusion models for image and audio generation in PyTorch.
Build machine learning demos and other web apps, in just a few lines of Python.
Client library for the BOINCAI Hub: manage repositories from your Python runtime.
BOINC AI JS.
Community library to run pretrained models from Transformers in your browser.
Experiment with over 200k models easily using the serverless tier of Inference Endpoints.
Easily deploy models to production on dedicated, fully managed infrastructure.
Parameter efficient finetuning methods for large models.
Easily train and use PyTorch models with multi-GPU, TPU, mixed-precision.
Fast training and inference of BOINCAI Transformers with easy to use hardware optimization tools.
Train and Deploy Transformers & Diffusers with AWS Trainium and AWS Inferentia via Optimum.
Fast tokenizers, optimized for both research and production.
Evaluate and report model performance easier and more standardized.
API to access the contents, metadata and basic statistics of all BOINCAI Hub datasets.
Train transformer language models with reinforcement learning.
Train and Deploy Transformer models with Amazon SageMaker and BOINCAI DLCs.
State-of-the-art computer vision models, layers, optimizers, training/evaluation, and utilities.
Simple, safe way to store and distribute neural networks weights safely and quickly.
Toolkit to serve Large Language Models.
AutoTrain API and UI.