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PyPI · #5538 most downloaded on PyPI
NeMo - a toolkit for Conversational AI
Last release 1 months ago
07 Aug 2026
Release timing varies
gaps range from 2 weeks to 4 months
Nearly every release is documented
notes for 60 of the last 60 stable releases
Nothing withdrawn
no release was ever pulled
7 years old
109 releases · first in 2019
find_unused_parameters should be False when training GPT: #3837
Increase lower bound due to security vulnerability by @ericharper :: PR: #3537
NOTE: From NeMo 1.7.0 onwards, NeMo containers will follow the YY.MM conversion for naming, where the YY.MM value is based on the base container. For additional information regarding NeMo containers, please visit : https://catalog.ngc.nvidia.com/orgs/nvidia/containers/nemo
docker pull nvcr.io/nvidia/nemo:22.01
One column per quarter.
Changed Apex not found error to warning to enable NLP models which aren't apex dependent when Apex isn't installed.
Fix embedding name for verifying speakers #3578
Repair arbitrary file or folder deletion vulnerability by @haby0 :: PR: #3362
Improvements:
Minor updates to expose speaker id, pitch, and duration on export of FastPitch #3192, #3207
Megatron GPT pre-training with tensor model parallelism #2975
@ericharper @michalivne @MaximumEntropy @VahidooX @titu1994 @blisc @okuchaiev @tango4j @erastorgueva-nv @fayejf @vadam5 @ekmb @yaoyu-33 @nithinraok @erhoo82 @tbartley94 @PeganovAnton @madhukarkm @yzhang123 (Please let us know if you have contributed to this release and we have missed you here.)
Improved speaker clustering #2729
@tango4j @titu1994 @paarthneekhara @nithinraok @michalivne @erastorgueva-nv @borisfom @blisc (some contributors may not be listed explicitly)
Multi-batch inference support for speaker diarization #2522
@pasandi20 @ekmb @nithinraok @titu1994 @ryanleary @yzhang123 @ericharper @michalivne @MaximumEntropy @fayejf (some contributors may not be listed explicitly)
Improve performance of speak clustering
@nithinraok @tango4j @jbalam-nv @titu1994 @MaximumEntropy @mchrzanowski @michalivne @jbalam-nv @fayejf @okuchaiev
(some contributors may not be listed explicitly)
import nemo.collections.nlp as nemo_nlp will result in an error. This will be patched in the upcoming version. Please try to import the individual files as a work-around.NeMo 1.1.0 release is our first release in our new monthly release cadence. Monthly releases will focus on adding new features that enable new NeMo Mo
NeMo 1.1.0 release is our first release in our new monthly release cadence. Monthly releases will focus on adding new features that enable new NeMo Models or improve existing ones.
@borisfom @MaximumEntropy @ericharper @aklife97 @titu1994 @ekmb @yzhang123 @blisc
(some contributors may not be listed explicitly)
NeMo 1.0.2 is a minor change over 1.0.0 adding version checks for Hydra dependency.
NeMo 1.0.2 is a minor change over 1.0.0 adding version checks for Hydra dependency.
NeMo 1.0.1 is a minor change over 1.0.0 adding proper version bounds for some external dependencies.
NeMo 1.0.1 is a minor change over 1.0.0 adding proper version bounds for some external dependencies.
NeMo 1.0.0 release is a stable version of "1.0.0 release candidate". It substantially improves overall quality and documentation. This update adds sup
NeMo 1.0.0 release is a stable version of "1.0.0 release candidate". It substantially improves overall quality and documentation. This update adds support for new tasks such as neural machine translation and many new models pretrained in different languages. As a mature tool for ASR and TTS it also adds new features for text normalization and denormalization, dataset creation based on CTC-segmentation and speech data explorer. These updates will benefit researchers in academia and industry by making it easier for them to develop and train new conversational AI models.
To install this specific version from pip do:
apt-get update && apt-get install -y libsndfile1 ffmpeg
pip install Cython
pip install nemo-toolkit['all']==1.0.0
This release contains major new models, features and docs improvements. It is a "candidate" release for 1.0.0.
This release contains major new models, features and docs improvements. It is a "candidate" release for 1.0.0.
To install from Pip do:
apt-get update && apt-get install -y libsndfile1 ffmpeg
pip install Cython
pip install nemo_toolkit['all']==1.0.0rc1
It adds the following model architectures:
In NLP collections, a neural machine translation task (NMT) has been added with Transformer-based models. This release includes pre-trained NMT models for these language pairs (in both directions):
For ASR task, we also added QuartzNet models, trained on the following languages from Mozilla's Common Voice dataset: Zh, Ru, Es, Pl, Ca, It, Fr and De. In total, this release adds 60 new pre-trained models.
This release also adds new NeMo tools for:
This version is not compatible with PyTorch 1.8.* Please use 1.7.* with it or use our container.
This release contains minor bug fixes over 1.0.0b2. It sets compatible version ranges for Hugging Face Transformers and Pytorch Lightning packages.
This release contains minor bug fixes over 1.0.0b2. It sets compatible version ranges for Hugging Face Transformers and Pytorch Lightning packages.
This release contains stability improvements and bug fixes. It also adds beam search support for CTC based ASR models.
This release contains stability improvements and bug fixes. It also adds beam search support for CTC based ASR models.
This version will not work with Hugging Face transformers library version >=4.0.0. Please make sure your transformers library version is transformers>=3.1.0 and <4.0.0.
Toolkit in an early version software.
Toolkit in an early version software. Breaking changes compared to previous version.
This release is a major re-design compared to previous version. All NeMo models and modules are now compatible out-of-the box with Pytorch and Pytorch Lightning. Every NeMo model is a LightningModule that comes equipped with all supporting infrastructure for training and reproducibility. Every NeMo model has an example configuration file and a corresponding script that contains all configurations needed for training. NeMo, Pytorch Lightning, and Hydra makes all NeMo models have the same look and feel so that it is easy to do Conversational AI research across multiple domains. New models such as Speaker verification and Megatron are added.
Toolkit in an early version software. Breaking changes compared to previous version.
All models and modules can be used anywhere torch.nn.Module is expected.
Nothing published for this version
Nothing published for this version
This release improves ease of use and adds new features
This release improves ease of use and adds new features
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Fixes an issue when distributed training would halt if Loss is NaN instead of skipping the batch
This is a bug fix release
This release improves overall stability of NeMo, revamps type system and adds new models
This release improves overall stability of NeMo, revamps type system and adds new models
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
Nothing published for this version
This release contains new features, new models and quality improvements for NeMo.
This release contains new features, new models and quality improvements for NeMo.
This is a quality improvement release for NeMo.
This is a quality improvement release for NeMo.
This is a quality improvement release for NeMo.
This is a quality improvement release for NeMo.
David Pollack (dhpollack), Harisankar Haridas (harisankarh), Dilshod Tadjibaev (antimora)
The first public release of NVIDIA Neural Modules: NeMo.
The first public release of NVIDIA Neural Modules: NeMo.
This release also includes nemo_asr'' and nemo_nlp'' collections for Speech Recognition and Natural Language Processing.
Please refer to the documentation here: https://nvidia.github.io/NeMo/
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