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} | # What does this PR do ?
Add FP8 support for SD training.
**Collection**: [multimodal/text_to_image/statble_diffusion]
# Changelog
- Add config argument - use_te_fp8 to switch between fp16 and fp8 training
- Add transformer engine fp8 layers to Stable diffusion Unet
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"This can be closed as PR gets merged",
"Thank you for the quick PR!"
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"Same issue in FSDP+SFT.\r\nThe loss is 3-4 times higher than TP, PP, and DP cases. I doubted fused_adam at first (currently, FSDP cannot apply distributed_fused_adam) but, fused_adam worked well except for FSDP.\r\n\r\n### Environment details\r\n\r\nDocker Container: `nvcr.io/nvidia/nemo:24.01.01.framework`\r\n\r\... | 2024-02-22T23:55:22 | 2024-05-29T08:39:16 | 2024-03-25T21:34:15 | COLLABORATOR | {
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We'd like to use FSDP when doing LoRA fine-tuning with large LLMs. We noticed in our experiments that the train loss when using FSDP vs. no FSDP is very different. With FSDP, the train loss is extremely high, but after turning off FSDP and doing a regular LoRA tuning, we see normal train loss c... | {
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clean up for specchllm | {
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"Thanks @titu1994 , I am using:\r\naccumulate_grad_batches=18\r\nbatch_size=15\r\n2 GPUs.\r\n So if I understand correctly, the global batch size = 18 * 15 * 2 = 540, right?",
"Yes that m... | 2024-02-22T18:12:25 | 2024-04-06T01:44:00 | 2024-04-06T01:44:00 | CONTRIBUTOR | {
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I'm trying to train a fastconformer model from scratch, I did manage to overfit for a small dataset, but it diverges for the full dataset, when I try a smaller dataset (30%) of the large it also diverges in what seems to be the exact same time:
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Add NeMo Audio Codec Models to the collection
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- Add audio codec 16kHz config
- Add NGC model to pretrained list
# Usage
### Automatically load the model from NGC
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"@stevehuang52 this problem basically happens when we try to resume 2nd time right ? ",
"> @stevehuang52 this problem basically happens when we try to resume 2nd t... | 2024-02-21T22:51:14 | 2024-03-23T03:14:17 | 2024-03-23T03:14:16 | COLLABORATOR | {
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} | # What does this PR do ?
Fix PTL2.2 saving multiple `*-last.ckpt` checkpoints in resumed training.
In current PTL2.2 [model_checkpoint.py](https://github.com/Lightning-AI/pytorch-lightning/blob/master/src/lightning/pytorch/callbacks/model_checkpoint.py#L783), it doesn't delete the previous `*-last.ckpt` checkpoi... | {
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PEFT better error message and doc
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- Better error message for using a different TP value for PEFT evaluation from training
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We're adding several features to enable audio-to-audio dataloading:
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} | null | null | null | I trained a Nemo ASR model (nemo.collections.asr.models.hybrid_rnnt_ctc_bpe_models.EncDecHybridRNNTCTCBPEModel) a few weeks ago using Nemo v1.21.0 and was able to decode with the .nemo model without any issues. Since then I updated my codebase and python environment to use v1.22.0. After that I tried to go back to expo... | {
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} | null | null | null | hi,
I have export the language identification model to onnx and I want to use it for inference.
how should I use this model for inference on an audio file?
how should be the format of my audio input?
is there any example or tutorial?
after using the following code:
```
import nemo
import nemo.collections.as... | {
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"I'm in the same situation. I get : \r\n\r\n```\r\n transcript = asr_model.transcribe(batch, batch_size=1)\r\n File \"/home/ubuntu/miniconda3/envs/nemo202403/lib/python3.10/site-packages/torch/utils/_contextlib.py\", line 115, in decorate_context\r\n return func(*args, **kwargs)\r\n File \"/home/ubuntu/min... | 2024-02-21T10:23:43 | 2024-04-22T01:45:30 | 2024-04-22T01:45:29 | NONE | {
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} | null | null | null | **Describe the bug**
I am trying to use the NeMo Canary ASR model for transcribing audio in memory.
However when i try to use the audio argument of the class like it is documented here: https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/asr/results.html#transcribing-inference
i get the error `Er... | {
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} | # What does this PR do ?
Add a description of the CTC-WS context-biasing method to the documentation.
**Collection**: [ASR]
# Changelog
- Rename docs/source/asr/asr_language_modeling.rst -> docs/source/asr/asr_language_modeling_and_customization.rst
- Add context-biasing description to docs/source/asr/asr_l... | {
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Reduce memory footprint by replacing torch.argsort. With my local sample, diarization pipeline works on 12GB. Without the patch, it failed with an error `torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.60 GiB. GPU 0 has a total capacty of 23.64 GiB of which 3.21 GiB is f... | {
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Add Gemma Support and Conversion Scripts
**Collection**: [NLP]
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- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
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# Jenkin... | {
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Add Gemma Model Support and Conversion Scripts
**Collection**: [NLP]
# Changelog
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# Usage
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```
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**Collection**: [Note which collection this PR will affect]
# Changelog
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Support relative audio paths in Lhotse `LazyNeMoIterator`
**Collection**: ASR
# Changelog
- Support relative audio paths in Lhotse `LazyNeMoIterator`
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
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"Solved the issue, by providing the ckpt path, could I ask why it doesn't work using \".nemo\" files?",
"This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days.",
"This issue was closed because it has been inactive for 7 days sin... | 2024-02-20T13:34:51 | 2024-04-26T14:56:11 | 2024-03-29T01:44:02 | CONTRIBUTOR | {
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**Collection**: [ASR]
# Changelog
- Add tutorials/asr/ASR_Context_Biasing.ipynb tutorial
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor gu... | {
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Code to enable video pretraining for NeVa.
[W&B Project](https://wandb.ai/joc/video_neva)
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
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"@dimapihtar @ericharper \r\nSame issue occurs when trying to load the distributed checkpoint for continued training / sft.\r\n\r\nLoading distributed checkpoint with a single A100 works fine, with gbs=1,tp=1,pp=1,mbs=1. \r\nWhen scaling to 8 gpus, and changing gbs to 8, loading the checkpoint fails.\r\n\r\nHas the... | 2024-02-20T02:09:45 | 2024-05-28T01:46:53 | 2024-05-28T01:46:52 | CONTRIBUTOR | {
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A clear and concise description of what the bug is.
I have an mcore distributed checkpoint trained with PP=1, TP=1. When running inference with this distributed checkpoint, when I set the TP to higher than 1, it results in exceptions and inconsistent hangs.
When running inference with mcor... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/8459 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/8459/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/8459/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/8459/events | https://github.com/NVIDIA/NeMo/issues/8459 | 2,142,727,118 | I_kwDOC_bI7s5_t2vO | 8,459 | Python 3.11 torch.jit.script segmentation fault | {
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"Probably related: https://github.com/pytorch/pytorch/issues/86566",
"Yikes. Fyi @tango4j @nithinraok @artbataev ",
"@dkurt What version of PyTorch do you use? What is the environment (OS, conda/pip, etc)?",
"@artbataev, Extremely apologize. Segmentation fault reproduced with Python `3.11.0rc1` and PyTorch 2.... | 2024-02-19T16:14:28 | 2024-02-20T11:02:23 | 2024-02-20T11:02:23 | NONE | {
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Segmentation fault when import asr:
```
$ python -c "from nemo.collections.asr.models.msdd_models import NeuralDiarizer"
Segmentation fault (core dumped)
```
`faulthandler` reports a problem with `@torch.jit.script` compilation: https://github.com/NVIDIA/NeMo/blob/df5a39583e31fd99bda37175... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/8458 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/8458/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/8458/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/8458/events | https://github.com/NVIDIA/NeMo/pull/8458 | 2,142,620,820 | PR_kwDOC_bI7s5nTUnR | 8,458 | FSDP support for GPT fine-tuning | {
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"jenkins",
"jenkins"
] | 2024-02-19T15:22:59 | 2024-02-28T17:18:29 | 2024-02-28T17:18:28 | COLLABORATOR | {
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"merged_at": "2024-02-28T17:18:28"
} | # What does this PR do ?
1) FSDP bug fix.
2) FSDP support for GPT fine-tuning.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code sni... | {
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"Hi, can you add me to the org/team ea-bignlp/ga-participants. I can't get any info about private repository, so i can't pull that container. Thanks you so much!",
"This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days.",
"This ... | 2024-02-19T07:50:05 | 2024-04-08T01:44:40 | 2024-04-08T01:44:40 | NONE | {
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training container image update to `nvcr.io/nvidia/nemo:24.01.framework`
but nemo inference container image is still in private repository `nvcr.io/ea-bignlp/ga-participants/nemofw-inference`
Is there a plan to migrate the nemo inference container ... | {
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"This issue was closed because it has been inactive for 7 days since being marked as stale."
] | 2024-02-18T22:17:39 | 2024-03-27T01:44:10 | 2024-03-27T01:44:09 | NONE | {
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Thank you | {
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I tried to use forced aligner to generate timestamps for my audio files, I got ctm results in tokens like this:
100001 1 0.00 0.44 \<b>
100001 1 0.44 0.04 WORD1
100001 1 0.48 0.20 \<b>
100001 1 0.68 0.04 WORD2
100001 1 0.72 0.20 \<b>
100001 1 0.9... | {
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"Also seeing this error.\r\n\r\nMy temporary workaround is to catch ValueErrors and just add a second or two of blank audio to the end of the file before re-processing which seems to work as a temporary stop-gap until this can be fixed.",
"This issue is stale because it has been open for 30 days with no activity.... | 2024-02-17T10:08:31 | 2024-06-19T01:54:08 | 2024-05-18T01:45:29 | NONE | {
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When I tried to generate timestamp with model: nvidia/parakeet-tdt-1.1b, I got following error,
ValueError: `char_offsets`: [{'char': [tensor(607, dtype=torch.int32)], 'start_offset': 28, 'end_offset': 29}....
call stack,
```
Traceback (most recent call last):
File "/tmp/inference/nvidi... | {
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} | null | null | null | **Is your feature request related to a problem? Please describe.**
- Can you explain, how to fine-tune Nvidia latest ASR models like Canary 1B and NeMo Parakeet ASR Models.
https://nvidia.github.io/NeMo/blogs/2024/2024-02-canary/
https://nvidia.github.io/NeMo/blogs/2024/2024-01-parakeet/
**Describe the soluti... | {
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- update audio_segment.py to allow duration is None
- add lhotse support for relative audio paths
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Integrating AMMO library to the project and providing utilities for quantizing models with Llama2 PTQ example.
Different quantization algorithms are available including **INT8 SmoothQuant**, **INT4 AWQ**, and **FP8**.
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Adds bug fixes to support TP, PP =and SP
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} | # What does this PR do ?
Fixes conversion script for NeMo to HF for mistral-7B.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
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"Running into a similar issue training the conformer large model \r\nin a docker container with the latest `nvcr.io/nvidia/nemo:23.10` image, on p2.16xlarge (V100 instances). What is your training environment like?",
"This is my docker container\r\n\r\n```\r\nnvcr.io/nvidia/clara/bionemo-framework:latest \"/wor... | 2024-02-16T15:40:24 | 2024-05-25T14:37:01 | 2024-03-26T01:44:06 | NONE | {
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I am using the default configs, code and data to train a model within BioNeMo framework. The timeout occurs at the middle of the training.
```
Epoch 0: 6%|██ | 32040/500150 [6:28:43<94:39:17, 1.37it/s, loss=2.6, v_num=95nc, reduced_train_loss=2.590, global_step=3.2e+4, consum... | {
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Updates the NeMo readme to include new generative ai focus and move domain centric info to domain readmes.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
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Add a one line overview of what this PR aims to accomplish.
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"@biscayan \r\n\r\nDo you remember how you come up with the model_stride_sec = 0.08? [Link to the line](https://github.com/biscayan/NeMo/blob/9f50dbdabed105d2649384e... | 2024-02-16T02:04:16 | 2024-05-21T23:57:18 | 2024-05-21T21:48:22 | NONE | {
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} | # What does this PR do ?
I closed a pull request #8341 because of lots of conflicts in the branch.
I tried to solve, but finally I deleted the branch, made new one, and add sign-off to the commit.
Sorry for my mistakes.
**Collection**: [Note which collection this PR will affect]
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} | # What does this PR do ?
Address mcore support transformer models instead of just decoder/GPT models.
**Collection**: [Note which collection this PR will affect]
# Changelog
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"There's a reason those decoding classes aren't modules. When rnnt was being developed it turned out there was a memory leak due to pt graph tracking and Autoregressive calls to the decoder joint. That's why .freeze(), .as_frozen() was developed in NeMos core to deal with that. \r\n\r\nI dunno if that reason is sti... | 2024-02-15T23:05:26 | 2024-02-28T23:40:35 | 2024-02-28T23:40:35 | COLLABORATOR | {
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@artbataev pointed out to me an issue with calling this when the model is using the cuda graph rnn-t decoder:
```
from nemo.collections.asr.models import ASRModel
import torch
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} | # What does this PR do ?
Unify HF converter scripts and arguments. Moved from https://github.com/NVIDIA/NeMo/pull/8307. Change target to main.
# Jenkins CI
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Add fix for ensemble model decoding.
**Collection**: ASR
# Changelog
- During addition of MultitaskAED decoding, condition to handle ConfidenseEnsembleModel was missed.
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
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Improvements for Canary:
- carry over custom keys when creating tarred manifests
- selectable text field in ASR eval
- get rid of prompt slicing, create proper inference prompts
**Collection**: ASR
# Changelog
- carry over custom manifest keys when creating tarred manifests
- s... | {
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GPU acceleration added,
Data loading optimization with adding multiprocessing,
Code refactoring started
+ Added support for running inside the docker container
@vsl9
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Hotfix
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Ad... | {
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"> Nice ! Thanks for the improvement !\r\n\r\nThanks, I'm merging.."
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} | # What does this PR do ?
Some distributed workloads can possibly be launched "manually" with `mpirun -n N python ...`. I'm adapting `nemo.utils.get_rank.py` module to take it into account and produce correct rank information in such cases.
Currently the below **rank_example.py** script (with [the project pattern ... | {
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Support Flashlight and Pyctcdecode decoding with pure KenLM and NeMo KenLM
Standardize API of CLI inference scripts
**Collection**: ASR
# Changelog
- Fix install script install_beamsearch_decoders.sh
- Create flashlight_lexicon file during sc... | {
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Add fix for ensemble model decoding.
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# Changelog
- During addition of MultitaskAED decoding, condition to handle ConfidenseEnsembleModel was missed.
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
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1) When a float `limit_val_batches` is passed by the user, the PR ensures that the `limit_val_batches` is cast to an equivalent int value and also makes sure the cast `limit_val_batches` is a multiple of num of microbatches as required by PTL >= 2.0.
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Bug fix in diarization scripts
# Changelog
- Call of `get_ctm_line function` in `create_new_ctm_entry` with `conf=0` raises error due to later type check, should be `conf=0.0`
- In function `create_manifest_with_alignments` the call of `get_seg_info_from_ctm_line` should return tuple `... | {
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} | # What does this PR do ?
Adding a few methods to support SD fine-tuning using DRaFT algorithm
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
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Address mcore support transformer models instead of just decoder/GPT models.
**Collection**: [Note which collection this PR will affect]
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} | # What does this PR do ?
This PR fixes the bug in `scripts/speaker_tasks/create_alignment_manifest.py`.
The `get_seg_info_from_ctm_line` function was outputing values in a wrong order.
Plus, confidence value could be set to `None` to prevent any type error issues.
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Support Flashlight and Pyctcdecode decoding with pure KenLM and NeMo KenLM
Standardize API of CLI inference scripts
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"This error seems like happening since the audio is containing 0 second of RTTM target evaluation duration. \r\nWe cannot reproduce the error unless we have access to the audio input.\r\n@RafalCer Could you check the rttm file you... | 2024-02-14T10:31:00 | 2024-05-08T18:26:39 | 2024-05-08T18:26:39 | NONE | {
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I am getting a `ZeroDivisionError: float division by zero` error when diarizing a very short short file with prior voice activity detection:
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return score_labels(
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
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This PR fixes the bug in `scripts/speaker_tasks/create_alignment_manifest.py`.
The `get_seg_info_from_ctm_line` function was outputing values in a wrong order.
Plus, confidence value could be set to `None` to prevent any type error issues.
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Enables FSDP when using PEFT during training/fine-tuning.
**Collection**: [NLP]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Jenkins CI
To run Jenkins, a NeMo User with write access must comment `jenkins` on the PR.
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} | # What does this PR do ?
Fix dreambooth data sampler issue
**Collection**: Multimodal
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
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replaces logging.error (actually not an error) with logging.info
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
tools
# Changelog
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} | # What does this PR do ?
Update Multimodal data preparation tutorial.
**Collection**: Multimodal
# Changelog
- Delete duplicate section
- Populate "TODO" links with actual links from toolkit doc and launcher.
# Jenkins CI
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Update Multimodal data preparation tutorial.
**Collection**: Multimodal
# Changelog
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# Jenkins CI
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} | # What does this PR do ?
Update the link used to download the video we use in the NFA tutorial.
**Collection**: tutorials
# Changelog
- Update link in the 2 places it appears in the notebook.
# Usage
N/A
# Jenkins CI
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Fixes link with `pubmed23n0009`
**Collection**: [NLP]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
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Update the link used to download the video we use in the NFA tutorial.
**Collection**: tutorials
# Changelog
- Update link in the 2 places it appears in the notebook.
# Usage
N/A
# Jenkins CI
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Mcore customization doc
**Collection**: [Note which collection this PR will affect]
# Changelog
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**Collection**: [ASR]
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Fixes breaking tutorial issue
**Collection**: [ASR]
# Changelog
- Minor tutorial fix to reflect WER changes
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**Collection**: [NLP]
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# Usage
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# Add a code snippet demonstrating how to use this
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I'm using Nemotron-3 deployed in Triton Inference server, I'm using this connector code with langchain:
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Fix dreambooth data sampler issue
**Collection**: Multimodal
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# Usage
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Fix dreambooth data sampler issue
**Collection**: Multimodal
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This PR fixes typo in documentation for MLFlow exp manager configuration.
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**Collection**: docs/source/core
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**Collection**: common (tokenizers)
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1) Adds support for dict data input type.
2) Adds changes for mock dataset.
3) Adds tests for 1 & 2.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
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} | # What does this PR do ?
Add Finetuning of Parakeet model with HF Datasets
**Collection**: ASR
# Changelog
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# Before your PR is "Ready for review"
**Pre checks**:
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This PR implements single video inference with a video dataloader fed through NeVA Image Encoder
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Adds properties required by megatron-core to NeMo tokenizers via the base TokenizerSpec class (see #8283).
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"This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days.",
"This issue was closed because it has been inactive for 7 days since being marked as stale."
] | 2024-02-09T18:08:51 | 2024-03-18T01:44:06 | 2024-03-18T01:44:05 | NONE | {
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} | null | null | null | Hello, I encountered this issue while trying to run the Online ASR tutorials on a PC, using python 3.10.13 and nemo-toolkit==1.23.0rc0.
SystemError: PY_SSIZE_T_CLEAN macro must be defined for '#' formats
From web results, this errors seems to happen when old packages don't support newer versions of Python, which ... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/8387 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/8387/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/8387/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/8387/events | https://github.com/NVIDIA/NeMo/pull/8387 | 2,127,623,884 | PR_kwDOC_bI7s5mgeX5 | 8,387 | Add fp8 support for SD/Update notebook paths | {
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"jenkins",
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} | # What does this PR do ?
Add FP8 support for SD training.
**Collection**: [multimodal/text_to_image/statble_diffusion]
# Changelog
- Add config argument - use_te_fp8 to switch between fp16 and fp8 training
- Add transformer engine fp8 layers to Stable diffusion Unet
- Update a few legacy paths in notebook ... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/8386 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/8386/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/8386/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/8386/events | https://github.com/NVIDIA/NeMo/issues/8386 | 2,127,318,969 | I_kwDOC_bI7s5-zE-5 | 8,386 | The learning process is interrupted for no apparent reason | {
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"The training script seems to be correct. We don't do any network op during validation, but maybe if you're using wandb somehow that crashed and caused a disconnect ?",
"I didn't install and use wandb.",
"> The training script seems to be correct. We don't do any network op during validation, but maybe if you'r... | 2024-02-09T15:02:55 | 2024-03-24T01:45:26 | 2024-03-24T01:45:25 | NONE | {
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} | null | null | null | **Describe the bug**
I start training with a ready ckpt 'QuartzNet15x5_ru--val_wer=0.3912-epoch=116.ckpt'
I start the training with the command 'nohup python command file_name.py > info_about_train.txt 2>&1 &'
After some time (from 1 to 10 epochs), the training is simply interrupted, regardless of the stage (train... | {
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