Models
Checkpoints and releases
None released yet. Here is what will ship and how to know when.
No checkpoint exists yet. NEST v2 has not been trained to completion, so there is nothing to download. An earlier version of this page carried a model table with word error rate numbers. That table was removed: those numbers were estimated from training loss, never measured by decoding, and were never real results. A checkpoint appears here only after it is trained and evaluated with free decoding on held-out subjects.
Planned releases
What ships, once it exists
Both NEST v2 heads instantiate and run today. Neither has completed training. Parameters below are counted from the code, not estimated.
| Model | Parameters | Input | Status | WER |
|---|---|---|---|---|
| NEST v2 CTC | 45.3M | 840-dim word features | Planned after GPU run | pending |
| NEST v2 BART | 184M total, 64.7M trainable | 840-dim word features | Planned | pending |
When a checkpoint is ready, it will publish on GitHub Releases and the Hugging Face Hub, together with the evaluation report that produced its WER.
Get notified
Two ways to hear about it first
Watch the repository
Watch releases on GitHub. The v2 checkpoint and its evaluation report publish there the moment training finishes.
Follow Discussions
Training progress, the GPU run, and open questions about the evaluation protocol are posted to GitHub Discussions as they happen.
Train your own today
Nothing is stopping you from running it yourself
The code, the ZuCo integration, and the training loop are public now. A quick test run on the CTC head verifies your setup in minutes; a full run needs a GPU. See the docs for installation and the rest of the commands.
python scripts/train_nest_v2.py --quick-test --model ctc
Follow the first checkpoint
Watch the repository for the v2 training run and the release that follows it.