Getting started

Quickstart

Install the client, authenticate, and pull your first checkpoint. Five minutes end to end on a machine with a single GPU.

Install

The client ships as a single wheel with optional extras for training and quantisation.

Install
pip install "osai[torch]"
osai login  # paste a token from Settings → Access tokens

Pull a model

Repositories are content addressed. A pull resolves the revision, verifies checksums and caches weights under ~/.cache/osai.

Pull a model
osai pull mistralai/Mistral-7B-Instruct-v0.3 --revision main

Generate

Any repository with a config.json loads through the auto classes; a chat template ships in the tokenizer.

Generate
from osai import pipeline

pipe = pipeline("text-generation", "mistralai/Mistral-7B-Instruct-v0.3")
print(pipe("Summarise rectified flow in two sentences.")[0]["text"])

Where next

Read the Inference API page for hosted endpoints, or Datasets for streaming corpora without local storage.