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I am using NeuralDiarizer with the default diar_infer_telephonic.yaml settings (nemo version 1.21.0). I am using it to diarize the real-life phone call recordings.
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} | # What does this PR do ?
Adding support for PTQ in nemo CLI.
Prerequisite: https://github.com/NVIDIA/NeMo/pull/10642.
**Collection**: [Note which collection this PR will affect]
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- Add specific line by line info of high level changes in this PR.
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} | # What does this PR do ?
Apply the following fixes to llm.generate
- load from context subdir instead of ckpt dir
- disabling initializing optimizer
- add logic to find exact McoreGPTModel
- require user to provide their own trainer for llm.generate
Usage:
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} | # What does this PR do ?
https://github.com/NVIDIA/NeMo/pull/10962 + lora
Running the example:
```
$ python3 NeMo/examples/llm/peft/hf.py --model /mnt/4tb/nemo_lite/phi3-mini-4k/
...
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**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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"I tested the changes on my local branch, didn't face any problems"
] | 2024-10-22T03:03:31 | 2024-10-22T16:33:55 | 2024-10-22T16:33:55 | COLLABORATOR | {
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} | # What does this PR do ?
This PR is fixing two issues
1) Currently, `process_audio.py` tries to override `sampler` even if `cfg.sampler` is an empty dict (so nothing to override)
2) Currently, `transcribe_speech.py` is crashing if using `audio_key != "audio_filepath"`
**Collection**: audio, ASR
# Changelog... | {
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📝 Please remember the following to-do's before merge:
- [ ] Verify the presubmit CI
🙏 Please merge this PR only if the CI workflow completed successfully. | {
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cherrypick for https://github.com/NVIDIA/NeMo/pull/10887
**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
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} | * Add __repr__ to Artifact
* nemo.lightning.io.artifact: represent strings as fdl.Config to avoid path adjustment during restoration
* t5 test minification
* Apply isort and black reformatting
---------
# What does this PR do ?
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"Hi @rogerwelo . Can you specify which Nemo container you are using?\n\nI've been using this one (`nvcr.io/nvidia/nemo:23.08`) for inference with this model. If you are using a different container, can you try it out?\n\nShuoyang",
"I ended up using Riva and followed the steps described [here](https://docs.nvidia... | 2024-10-21T17:31:23 | 2024-10-29T10:40:31 | 2024-10-29T10:40:29 | NONE | {
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I'm using the [Megatron Multilingual En Any 500M model](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/megatronnmt_en_any_500m) with [this example script](https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/machine_translation/nmt_transformer_infer_megatron.py).
I got the script to work in a [Nemo... | {
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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
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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."
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I am trying to convert the default `mamba.nemo` file (I converted [form huggingface](https://huggingface.co/nvidia/mamba2-8b-3t-4k/tree/main) .pt to .nemo) to have `tensor_parallel=4`. I have been following the [documentation here](https://docs.nvidia.com/nemo-framework/user-guide/latest/llms/mamb... | {
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**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 cod... | {
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} | # What does this PR do ?
Can be invoked with `nemo` or via the example
```
nemo llm pretrain --factory 'HfAutoModelForCausalLM(model_name="meta-llama/Llama-3.2-1B", num_gpus_per_node=1)'
```
the example:
```
cd examples/llm/sft/
python3 hf.py --model=meta-llama/Llama-3.2-1B --devices=1 --strategy=ddp
```
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CI-passed for DDP test= https://github.com/NVIDIA/NeMo/actions/runs/11409221189/job/31749224039
**Collection**: [Note which collection this PR will affect]
# Changelog
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- Change uses "sliding_window" arg in HF ckpt config to inform window_size. This makes it compatible with all sizes: 2B, 9B and 27B
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* The forward pass in Gemma 2 passes runtime_gather_output
* Leads to unexpected keyword arg error while finetuning gemma 2 2b without it
**Collection**: nlp/models/language_modeling/megatron/gemma2
# Changelog
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📝 Please remember the following to-do's before merge:
- [ ] Verify the presubmit CI
🙏 Please merge this PR only if the CI workflow completed successfully. | {
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} | # What does this PR do ?
Add model config validations for NeMo 2.0
**Collection**: llm
# Changelog
- Added training and fine-tuning config validation basics for NeMo 2.0.
- Added unit tests for config validation.
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} | # What does this PR do ?
Aim of this PR is to push a tutorial of training speech enhancement models with online augmentation to NeMo.
**Collection**: audio
# Changelog
- New notebook file with the tutorial added to tutorials/audio/speech_enhancement
- New configuration file for the training "masking" model... | {
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"> Thanks for this!\r\n> \r\n> Actually, the story is that I used to require model_downsample_factor to be in the config, but then I made some logic to calculate it, so that the user doesn't need to worry about it. The logic is here: https://github.com/NVIDIA/NeMo/blob/b6c3c0d5d41d2c695e6a1b23aa573e867b0ec729/tools... | 2024-10-18T15:43:00 | 2024-11-10T02:00:35 | 2024-11-10T02:00:34 | COLLABORATOR | {
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
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# Usage
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} | # What does this PR do ?
Extra changes just for cleanup purposes related to https://github.com/NVIDIA/NeMo/pull/10904, isolated here to facilitate review for main functionalities.
**Collection**: NLP
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentia... | {
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"this was solved in `r2.0.0rc1`",
"please install `!pip install huggingface-hub==0.23.3` ",
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} | null | null | null | **Describe the bug**
NeMo is not loading a ASR model I wanted to run because of internal dependency issues on HuggingFace Hub.
**Steps/Code to reproduce bug**
Colab Link: [colab link](https://colab.research.google.com/drive/1JqMW-JkyHJ61UOFO9eQhoHkQx6I3cH05?usp=sharing)
```python
!pip install nemo_toolkit['all']
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"Thanks for reporting this bug, will look into it asap & push a fix.",
"Hi this has been fixed in https://github.com/NVIDIA/NeMo/pull/11081 please give it a try, will be merged soon. Thanks."
] | 2024-10-18T09:20:42 | 2024-10-30T12:55:13 | 2024-10-30T12:55:13 | NONE | {
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} | null | null | null | **Describe the bug**
A clear and concise description of what the bug is.
**Steps/Code to reproduce bug**
```
nemorun llm import llama3_8b hf://meta-llama/Meta-Llama-3-8B -y
nemorun llm export ~/.cache/nemo/models/meta-llama/Meta-Llama-3-8B/context hf exp/PreTrain/export_llama3_8b -y
```
error
```
Dry run for task n... | {
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"@Victor49152 Hi, Can you help me? I just used the config provided in the NeMo/examples/multimodal/text_to_image/stable_diffusion/conf and follow the tutorials.\nI also use the nemo docker to run sd_xl_infer.py，and is still noise output image. ",
"Thanks for your post. Could you please check the log executing '... | 2024-10-18T08:56:38 | 2024-12-13T02:06:08 | 2024-12-13T02:06:08 | NONE | {
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I follow the [tutorial](https://github.com/NVIDIA/NeMo/blob/main/tutorials/multimodal/SDXL%20Quantization.ipynb) convert a model download from https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/unet/diffusion_pytorch_model.safetensors.
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"> 3e3e39b\r\n\r\nSure, I made the changes here: [3e3e39b](https://github.com/NVIDIA/NeMo/pull/10934/commits/3e3e39b5e1a93a85431333eafc74d80f4f4942ae)\r\nI have also removed the `drop_last` arg that I have added in https://github.com/NVIDIA/NeMo/pull/10837 since we can use the dataloader `mode` to avoid dropping th... | 2024-10-17T21:49:59 | 2024-10-29T00:24:55 | 2024-10-29T00:24:55 | CONTRIBUTOR | {
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} | # What does this PR do ?
### NeMo `MegatronDataSampler` is not tracking the `batch_indices`.
In BioNeMo 2.0 we use `PredictionWriter` callback of `BasePredictionWriter` that supposed to capture the `batch_indices` from dataloader's batch sampler and predictions from `predict_step` of the Lightning module. However... | {
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"@pzelasko Ive added the AIS check, as well as a flag in cluster config `check_ais_paths` which can be disabled (via config or commandline) in case folks want to preserve speed instead of doing path checks. ",
"[🤖]: Hi @titu1994 👋,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/Ne... | 2024-10-17T20:52:34 | 2024-12-10T02:06:21 | 2024-12-10T02:06:20 | COLLABORATOR | {
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Adds NeMo run support to ASR and common utilities for Run to common collections
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} | [🤖]: Hi @hemildesai 👋,<br><br>we've cherry picked #10914 into `r2.0.0` for you! 🚀<br><br>Please review and approve this cherry pick by your convenience\! | {
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} | # What does this PR do ?
Add environment markers according to [PIP documentation](https://pip.pypa.io/en/stable/reference/requirement-specifiers/) for optional requirements not installable on MacOS.
This fixes `pip install -e ".[all]"` on MacOS.
**Collection**: [Note which collection this PR will affect]
# Ch... | {
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Implemented ClipScoreFusion model (UniIR) which leverages Clip models for multimodal retrieval tasks
**Collection**: [Note which collection this PR will affect]
multimodal
# Usage
```python
model = MegatronCLIPScoreFusionModel(cfg.model, trainer)
```
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merge base model and lora adapter in nemo2
**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
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* EMMeTT (optimized training) support for SpeechLLM
* Support for joint audio and text training for `modular_models.py` and `modular_t5_models.py`
* Dedicated `estimate_token_bins.py` and `oomptimizer.py` in `scripts/speech_llm`.
* D... | {
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Add performance optimizations as a param
**Collection**: [llm]
# Changelog
```
if performance_mode:
recipe = pretrain_performance_optimizations(recipe)
```
# Usage
```python
from nemo.collections.llm.recipes.llama3_8b import pretrain_recipe
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} | # What does this PR do ?
Re-organizing inference pipeline in NeMo 2.0 for support both decoder and encoder-decoder (and other models).
Tested with GPT and T5.
**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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📝 Please remember the following to-do's before merge:
- [ ] Verify the presubmit CI
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Remove opencc upperbound
**Collection**: [nlp]
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# Usage
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} | * call __post_init__ after altering config values
* test fix
* turn off SP
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Warning for missing FP8 checkpoint support for vLLM deployment.
**Collection**: NLP
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} | # What does this PR do ?
* Update default pruning parameters based on optimal results
* Disable `sequence_parallel` by default since it does not work with pipeline parallel
* Add an option to prune `num_layers` (depth) as well
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add sp... | {
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} | # What does this PR do ?
Improve performance of mask calculations.
**Collection**: VLM
# 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
```
# GitHub ... | {
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I am wondering if the scripts implemented in Mamba Megatron pipeline parallel will be possibly used inside Nemo? Specifically Mamba Megatron supports converting Mamba both to Tensor Parallel & Pipeline Parallel [at here](https://github.com/NVIDIA/Megatron-LM/blob/main/tools/checkpoint/hybrid_conversion.py). The p... | null | {
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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."
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```
Follow the steps from [here](https://nemo-framework-tme.gitlab-master-pages.nvidia.com/documentation/user-guide/latest/llms/gemma/dataprep.html) to obtain and preprocess t... | {
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"It looks like github action uses a container with an older version of TE, so the new checkpoint i added couldn't be loaded. I'll revert to the old checkpoints for now",
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} | # What does this PR do ?
1. Save packed dataset in different folders according to the model name, so that different packed datasets don't clash with each other
2. Fix hanging if preparing packed data before a multi-gpu training session
3. Raise mbs>1 error and provide suggestion to user instead of automatically ch... | {
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**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
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} | [🤖]: Hi @malay-nagda 👋,<br><br>we've cherry picked #10853 into `r2.0.0` for you! 🚀<br><br>Please review and approve this cherry pick by your convenience\! | {
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PR to support nemo 2.0 ckpt in TRT-LLM export
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"Update on the procedure I'm following:\n- I use the Nemo framework 24.07 image\n- Launch a container with the image (witha couple of volumes): docker run --runtime=nvidia --gpus all -it --rm \\\n -v /mnt/shared_demos/dreambooth/nemo:/opt/NeMo \\\n -v /mnt/shared_models/huggingface/cache/hub/models--runwayml... | 2024-10-15T07:04:50 | 2024-11-24T02:06:03 | 2024-11-24T02:06:02 | NONE | {
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1. Fix assertion error due to "context" folder in base model checkpoint
2. Fix tokenizer loading issue during 3rd restart (First time training: tokenizer is loaded from base model and saved. Second time training: tokenizer is loaded from first checkpoint, but is not saved if the first check... | {
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