| --- |
| license: apache-2.0 |
| base_model: yunyangx/efficient-track-anything |
| tags: |
| - mirror |
| - cuvis-ai |
| - efficienttam |
| - video-object-segmentation |
| --- |
| |
| # EfficientTAM checkpoints (mirror) |
|
|
| Byte-identical mirror of [`yunyangx/efficient-track-anything`](https://huggingface.co/yunyangx/efficient-track-anything) at revision `9bdd8ab585b19ef95f9c9ed847ac9478301890b4` (code and licence: <https://github.com/yformer/EfficientTAM>) for the |
| [Cuvis.AI](https://github.com/cubert-hyperspectral/cuvis-ai) plugins. No fine-tuning, |
| conversion or re-serialization: the files below are the upstream release as published, |
| with the upstream licence text in `LICENSE`. |
|
|
| ## Why this mirror exists |
|
|
| Cuvis.AI provisions model weights once into a shared cache (`download-model download |
| <name>` from `cuvis-ai-core`) and then runs its pipelines in an offline, token-free |
| runtime that only reads that cache. Hosting the exact upstream files under the |
| `cubert-gmbh` organisation makes that provisioning reproducible (commit-pinned and |
| sha256-verified) and takes the per-user Hugging Face account and token out of the |
| users' path. |
|
|
| ## Files and provenance |
|
|
| | File | Upstream source | Upstream revision / id | sha256 | Size | |
| |---|---|---|---|---| |
| | `efficienttam_s.pt` | `yunyangx/efficient-track-anything` / `efficienttam_s.pt` | `9bdd8ab585b19ef95f9c9ed847ac9478301890b4` | `2b572be30d9e96ee29c8d785fe157c6b079ede7d56fbc8a3671d4120e63c89cd` | 136.4 MB | |
| | `efficienttam_ti.pt` | `yunyangx/efficient-track-anything` / `efficienttam_ti.pt` | `9bdd8ab585b19ef95f9c9ed847ac9478301890b4` | `acbb17b28cca1f860acee09c9ecb6efdb732080dc7a85a07292c31813175fa7d` | 71.6 MB | |
| | `efficienttam_s_512x512.pt` | `yunyangx/efficient-track-anything` / `efficienttam_s_512x512.pt` | `9bdd8ab585b19ef95f9c9ed847ac9478301890b4` | `67b5840012737ed2c94a4cb8787c5c1b27b3a946045d2e602e65ef77230b6085` | 136.4 MB | |
| | `efficienttam_ti_512x512.pt` | `yunyangx/efficient-track-anything` / `efficienttam_ti_512x512.pt` | `9bdd8ab585b19ef95f9c9ed847ac9478301890b4` | `7d4d652a465f0081391050932f45d8a66768ccc99c8ea393ce8a5927e83f3b9b` | 71.6 MB | |
| | `LICENSE` | <https://raw.githubusercontent.com/yformer/EfficientTAM/main/LICENSE> | n/a (URL; sha256 pinned) | `c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4` | 11.4 kB | |
|
|
| Mirrored on 2026-09-04 by Cubert GmbH from the sources above. The sha256 values are the |
| upstream values; `tools/mirror_weights.py check` in `cuvis-ai-core` re-verifies this |
| repository against them and against the upstream licence text. |
|
|
| ## Licence |
|
|
| Apache License 2.0. The `LICENSE` file is the upstream licence text taken verbatim |
| from <https://github.com/yformer/EfficientTAM> (the upstream Hugging Face repository carries the `apache-2.0` tag but ships no LICENSE file) at the mirror date. Copyright remains with the upstream authors; Cubert |
| GmbH claims no rights in these files. |
|
|
| ## Usage with Cuvis.AI |
|
|
| ```text |
| uv run download-model download efficienttam_s |
| uv run download-model download efficienttam_ti |
| uv run download-model download efficienttam_s_512x512 |
| uv run download-model download efficienttam_ti_512x512 |
| ``` |
|
|
| `download-model` (from `cuvis-ai-core`) provisions the file into the shared Hugging |
| Face cache and verifies its sha256. From cuvis-ai-core 0.16.0 on, |
| `ModelWeights.resolve("<name>")` returns the cached path and the `cuvis-ai-rtsam2` nodes |
| resolve their weights through it, so a pipeline needs no manual step once the |
| weights are provisioned; earlier plugin releases still fetch from their original |
| upstream sources. |
|
|
