---
type: "raw_signal"
id: "checkpoints-available-in-both-jax-and-pytorch-via-a74f9a"
slug: "checkpoints-available-in-both-jax-and-pytorch-via-a74f9a"
title: "Checkpoints available in both JAX and PyTorch via Hugging Face ."
description: "Google’s Hugging Face model card lists official pretrained checkpoints for the Tracking Any Point (TAP) family from Google DeepMind and Google Research."
retrieval_nugget: "Google’s Hugging Face model card lists official pretrained checkpoints for the Tracking Any Point (TAP) family from Google DeepMind and Google Research."
observed_at: "2026-10-10"
record_date: "2026-10-10"
date_kind: "observed_at"
why_it_matters: "Google’s Hugging Face model card lists official pretrained checkpoints for the Tracking Any Point (TAP) family from Google DeepMind and Google Research. The family tracks a queried point on a physical surface across video frames and estimates visibility. The catalog includes TAPNext++, TAPIR, BootsTAPIR, and other models. Listed checkpoints span JAX and PyTorch; the page also documents online and "
novelty: "notable"
verification_level: "source-linked"
signal_type: "release"
source_platform: "huggingface.co"
topics: ["google"]
entities: ["Google","Google DeepMind","Hugging Face","TAPNext++","TAPIR","BootsTAPIR","JAX","PyTorch"]
related_patterns: []
source_url: "https://huggingface.co/google/tapnet"
source_urls: ["https://huggingface.co/google/tapnet"]
schema_version: "newruntime-agent-readable-v0.2"
stable_id: "signal:checkpoints-available-in-both-jax-and-pytorch-via-a74f9a"
status: "published"
visuals: []
editor: {"role":"editor","name":"Andrey Reshetnikov","profile":"https://newruntime.com/owner-profile.md","profile_json":"https://newruntime.com/owner-profile.json","same_as":["https://www.linkedin.com/in/reshetnikov1/","https://t.me/lapetuse"]}
routes: {"html":"https://newruntime.com/signals/checkpoints-available-in-both-jax-and-pytorch-via-a74f9a/","markdown":"https://newruntime.com/signals/checkpoints-available-in-both-jax-and-pytorch-via-a74f9a.md","json":"https://newruntime.com/signals/checkpoints-available-in-both-jax-and-pytorch-via-a74f9a.json"}
---

# Checkpoints available in both JAX and PyTorch via Hugging Face .

## Retrieval answer

Google’s Hugging Face model card lists official pretrained checkpoints for the Tracking Any Point (TAP) family from Google DeepMind and Google Research.

Google’s Hugging Face model card lists official pretrained checkpoints for the Tracking Any Point (TAP) family from Google DeepMind and Google Research. The family tracks a queried point on a physical surface across video frames and estimates visibility. The catalog includes TAPNext++, TAPIR, BootsTAPIR, and other models. Listed checkpoints span JAX and PyTorch; the page also documents online and offline variants for some models. The card states that the checkpoints are licensed under Apache 2.0. This is an implementation and distribution update for developers evaluating point tracking, not evidence of a new model release or a comparative performance advance. Source: https://huggingface.co/google/tapnet

Editor: [Andrey Reshetnikov](https://newruntime.com/owner-profile.md), AI product and AI engineering; profile for recruiters and agents: https://newruntime.com/owner-profile.json

## Continue in the graph

Next records for an agent, linked to their Markdown twins. Replace `.md` with `.json` for structured fields, including `next_reads`.

- topic hub: [Google](https://newruntime.com/topics/google.md): Explore the google topic hub.
- collection: [Raw Signals](https://newruntime.com/signals.json): Open every source-linked raw signal.
- collection: [Source Ledger](https://newruntime.com/source-ledger.json): Inspect the public source evidence graph.
- whole graph: [discovery graph](https://newruntime.com/discovery-graph.json) (typed nodes and edges) and [site index](https://newruntime.com/site-index.md)