renwei2024/nemo-github-issues huggingface dataset:
ci: Set bump-branch to weekly
State: closed | Pull request: yes
Labels: name: CI

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chore(beep boop 🤖): Bump `MCORE_TAG=c7bf403...` (2025-01-18)
State: closed | Pull request: yes
Labels: name: Run CICD

name: no-fail-fast

🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=c7bf403ba37ce7ca739a025accac232c75a38966`.  

📝 Please remember the following to-do's before merge: 
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[🤖]: Hi @ko3n1g 👋,

We wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/12846160709) for this PR just finished successfully

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We wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/12846160709) for this PR just finished successfully

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Update PyTorch-cuda version in readme
State: open | Pull request: yes



# What does this PR do ?

Updating pytorch-cuda version to 12.1 as shown in https://docs.nvidia.com/nemo-framework/user-guide/latest/installation.html

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ci: Prune dangling images
State: closed | Pull request: yes
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build: Add `sox` to SDE
State: open | Pull request: yes
Labels: name: r2.1.1

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@vsl9 @ekmb could you please review and approve this PR? thanks!
KV-cache for T5 model
State: open | Pull request: yes
Labels: name: NLP

# What does this PR do?
Improve the T5 generation related issues and T5 attention mask bugs. This PR should be used with https://github.com/NVIDIA/Megatron-LM/pull/1358

**Collection**: nlp T5

# Changelog 
- Add kv-cache mechanism for Megatron-core T5 model.
- Fix the attention mask bugs for Megatron-core local implementations (when mcore_t5 is true, and transformer_engine is False)
- Improve the generation of T5 to be better aligned with that in GPT

# Usage
* Implement kv-cache in generation of T5, improving its efficiency
* Fix local mcore t5 model attention mask bugs (not from transformer_engine)
* In original T5 decode method, you can only generate fix length sequence, even when the EOS token is generated, it will still generate tokens until the predefined number of tokens are reached, which is very inconvenience and inefficient. This pull request raise enables variable length generation.

```python
python examples/nlp/language_modeling/tuning/megatron_gpt_finetuning.py <datasets and checkpoints override>
```

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Disable tests that download datasets from web
State: closed | Pull request: yes
Labels: name: CI

name: Run CICD

name: no-fail-fast

# What does this PR do ?

Disable tests that download datasets from the web to avoid unstable tests (e.g. remote host goes down).

TODO: store dataset locally.

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[🤖]: Hi @akoumpa 👋,

We wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/12823805985) for this PR just finished successfully

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[DRAFT] Fix BERT1 Dependency 
State: open | Pull request: yes
Labels: name: CI

# What does this PR do ?

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fix convert_llama_hf_to_nemo.py llama31 argument
State: open | Pull request: yes

# What does this PR do ?

Fix conversion script arguments. The original script using type=bool convert empty strings to False and non-empty strings to True. Might not be an ideal way of using it.

**Collection**: NLP

# Changelog 
- Fix convert_llama_hf_to_nemo script --llama31 arguments.

# Usage

```shell
$ scripts/checkpoint_converters/convert_llama_hf_to_nemo.py --llama31  # when it is llama31
$ scripts/checkpoint_converters/convert_llama_hf_to_nemo.py                  # when it is not llama31
```



<!-- pylint-output-strict-mode-false -->

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---

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```
************* Module convert_llama_hf_to_nemo
scripts/checkpoint_converters/convert_llama_hf_to_nemo.py:63:0: C0301: Line too long (218/119) (line-too-long)
scripts/checkpoint_converters/convert_llama_hf_to_nemo.py:46:0: C0116: Missing function or method docstring (missing-function-docstring)
scripts/checkpoint_converters/convert_llama_hf_to_nemo.py:75:0: C0116: Missing function or method docstring (missing-function-docstring)
scripts/checkpoint_converters/convert_llama_hf_to_nemo.py:129:0: C0116: Missing function or method docstring (missing-function-docstring)

-----------------------------------
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Add function calling SFT NeMo2.0 tutorial
State: open | Pull request: yes

# What does this PR do ?

Add function calling SFT NeMo2.0 tutorial.

**Collection**: NLP

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- Add specific line by line info of high level changes in this PR.

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Use empty dict instead of none to load only metadata from dist ckpt
State: open | Pull request: yes
Labels: name: Run CICD

# What does this PR do ?

Use empty dict instead of none to load only metadata from dist ckpt, due to change in mcore commit https://github.com/NVIDIA/Megatron-LM/commit/31e8bfa926ca05a3b70a48d3ed6b86410a85a262.
(Applying the same fixing PR in the release branch: https://github.com/NVIDIA/NeMo/pull/11782)

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[🤖]: Hi @huvunvidia 👋,

We wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/12804396135) for this PR just finished successfully

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Support both Path and str for APIs
State: closed | Pull request: yes
Labels: name: Run CICD

# What does this PR do ?

APIs may need to be wrapped in `run.Partial`. `pathlib.Path` cannot be wrapped in `run.Config`, so our APIs should support taking either `pathlib.Path` or `str`.

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<!-- pylint-output-strict-mode-false -->

beep boop 🤖: 🙏 The following files have warnings. In case you are familiar with these, please try helping us to improve the code base.

---

Your code was analyzed with PyLint. The following annotations have been identified:

```
************* Module nemo.collections.llm.api
nemo/collections/llm/api.py:583:0: C0116: Missing function or method docstring (missing-function-docstring)

-----------------------------------
Your code has been rated at 9.96/10
```

---

Mitigation guide:

* Add sensible and useful docstrings to functions and methods
* For trivial methods like getter/setters, consider adding `# pylint: disable=C0116` inside the function itself
* To disable multiple functions/methods at once, put a `# pylint: disable=C0116` before the first and a `# pylint: enable=C0116` after the last.

By applying these rules, we reduce the occurance of this message in future.

Thank you for improving NeMo's documentation!

[🤖]: Hi @maanug-nv 👋,

We wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/12813976197) for this PR just finished successfully

So it might be time to merge this PR or get some approvals

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chore(beep boop 🤖): Bump `MCORE_TAG=004fbcb...` (2025-01-16)
State: closed | Pull request: yes
Labels: name: Run CICD

🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=004fbcb30355d6d5336989fcdd6683fa5cd4d1c0`.  

📝 Please remember the following to-do's before merge: 
- [ ] Verify the presubmit CI  

🙏 Please merge this PR only if the CI workflow completed successfully.

[🤖]: Hi @ko3n1g 👋,

We wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/12813564036) for this PR just finished successfully

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Update cicd-main.yml
State: closed | Pull request: yes
Labels: name: CI

# What does this PR do ?

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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# Additional Information
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Run nsys callback on GBS not on MBS
State: closed | Pull request: yes
Labels: name: Run CICD

# What does this PR do ?

`get_current_epoch_step` tracks optimizer's current step (since the callback's start/end-step are in GBS). 
However, `on_train_batch_start` is called on every batch, therefore it is possible that it enters `if current_step == self._nsys_profile_start_step` and calls `emit_nvtx` multiple times.

This PR adds a boolean variable to prevent it from entering on each MBS.

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* Related to # (issue)


[🤖]: Hi @akoumpa 👋,

We wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/12834928205) for this PR just finished successfully

So it might be time to merge this PR or get some approvals

I'm just a bot so I'll leave it you what to do next.

//cc @pablo-garay @ko3n1g
Add nemo1 to nemo2 conversion for neva
State: open | Pull request: yes

# What does this PR do ?

Update conversion script to handle neva nemo1 to nemo2 conversion for llava 1.5 7b and 13b. It assumes the "vision_model" is frozen (i.e. not trainable) in nemo1. 
If vision model is trainable this script won't work correctly. 

**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 
```

# GitHub Actions CI

The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.

The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
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**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Removes tensorstore 0.1.45 pin from requirements_deploy.txt
State: closed | Pull request: yes
Labels: name: Run CICD

# What does this PR do ?

Removes the pin from tensorstore 0.1.45 from requirements_deploy.txt, since the issue was fixed in 0.1.47.

**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 snippet demonstrating how to use this 
```

# GitHub Actions CI

The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.

The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Chore: Update requirements.txt
State: open | Pull request: yes

When only using/installing the speech data explorer, pandas is not installed but needed to execute the tool. To stream line the process I edited the requirements.txt

# What does this PR do ?

It should help to streamline the process of installing the requirements, since pandas is used but not installed with the original file.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Added: "pandas" to line 11

# Usage
* When only using the Speech data explorer, in a new python enviroment.

# GitHub Actions CI

The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.

The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [x] Did you write any new necessary tests?
- [x] Did you add or update any necessary documentation?
- [x] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Fix typo ASR tutorial.
State: open | Pull request: yes
Labels: name: ASR

# What does this PR do ?

Fix tutorial typo

**Collection**: None

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

# GitHub Actions CI

The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.

The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [x] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
chore(beep boop 🤖): Bump `MCORE_TAG=c1cafa1...` (2025-01-15)
State: closed | Pull request: yes
Labels: name: Run CICD

🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=c1cafa1c19f9b7a014a0bc11c1ddbc13f739f086`.  

📝 Please remember the following to-do's before merge: 
- [ ] Verify the presubmit CI  

🙏 Please merge this PR only if the CI workflow completed successfully.
`prepare_energon_dataset.py` is supposed to save encoded latents but reconstructed videos are saved instead.
State: open | Pull request: no
Labels: name: bug

**Describe the bug**

According to https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/diffusion/data/readme.rst, `prepare_energon_dataset.py` is supposed to save encoded latents. However, it save the reconstructed videos instead. 

**Steps/Code to reproduce bug**
`torchrun --nproc_per_node=8 nemo/collections/diffusion/data/prepare_energon_dataset.py`


** Reason **
Autoencoder's forward function is called [here](https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/diffusion/data/prepare_energon_dataset.py#L219), which first encode the latents and then decode the latents, as shown [here](https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/common/video_tokenizers/cosmos_tokenizer.py#L205).

`autoencoder.encode` should be called instead.

 




@zpx01 can you take a look?

@Sy-Zhang can you try changing the following line:
https://github.com/NVIDIA/NeMo/blob/1626ddded63af1fe82b0bee482fba44c57b8203d/nemo/collections/common/video_tokenizers/cosmos_tokenizer.py#L205

to this:

`output_tensor = self.encode(input_tensor)`

I think this will temporarily fix your issue. We are going to have a large revision of the code soon, so this will not be an issue moving forward.
Add Minitron pruning example for NeMo 2.0
State: open | Pull request: yes

# What does this PR do ?

Add Minitron pruning example for NeMo 2.0

**Collection**: N/A

# Changelog 
- Add Minitron pruning example for NeMo 2.0

# Usage
* You can potentially add a usage example below

```python
torchrun --nproc_per_node 8 prune.py \
        --devices 8 \
        --tp_size 1 \
        --pp_size 8 \
        --restore_path <path/to/llama3.1-8b-nemo2> \
        --seq_length 8192 \
        --data_paths 30 path/to/dataset_1_prefix 70 path/to/dataset_2_prefix \
        --prune_ffn_hidden_size 9216 \
        --prune_hidden_size 3072 \
        --prune_num_attention_heads 32 \
        --prune_num_query_groups 8 \
        --save_path llama3.1-8b-width-pruned
```

# GitHub Actions CI

The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.

The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Optical Flow classifier
State: open | Pull request: no

Hello, NVIDIA team!

In the [Cosmos paper](https://research.nvidia.com/publication/2025-01_cosmos-world-foundation-model-platform-physical-ai) specifically in Section 3.3.1 "Motion Filtering" ViT-based optical flow classifier is mentioned. I was wondering if the weights for this model are publicly available or if there are plans to release them as part of data curation pipeline.

Thank you for your time and assistance!
Adding serialization to all Auto* obj by following #11645 PR
State: open | Pull request: yes

# What does this PR do ?

A draft based on PR version #11645, built on top of the latest code from GitHub.

**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 snippet demonstrating how to use this 
```

# GitHub Actions CI

The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.

The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to #11645 


<!-- pylint-output-strict-mode-true -->

beep boop 🤖: 🚨 The following files must be fixed before merge!

---

Your code was analyzed with PyLint. The following annotations have been identified:

```
************* Module nemo.lightning.io.artifact.hf_auto
nemo/lightning/io/artifact/hf_auto.py:92:0: C0301: Line too long (139/119) (line-too-long)

-----------------------------------
Your code has been rated at 9.74/10
```

---

Mitigation guide:

* Add sensible and useful docstrings to functions and methods
* For trivial methods like getter/setters, consider adding `# pylint: disable=C0116` inside the function itself
* To disable multiple functions/methods at once, put a `# pylint: disable=C0116` before the first and a `# pylint: enable=C0116` after the last.

By applying these rules, we reduce the occurance of this message in future.

Thank you for improving NeMo's documentation!
Cosmos support
State: open | Pull request: no

It seems that the fine-tuning training for Cosmos can only be done in the nvcr.io/nvidia/nemo:cosmos.1.0 image environment. I couldn't find the relevant code on Nemo's GitHub. I would prefer not to download an extra image again. When will this Cosmos code be updated on GitHub?

We are currently in the process of merging Cosmos related changes to the main branch in the NeMo repository.
ETA: ~2 weeks
chore(beep boop 🤖): Bump `MCORE_TAG=6486203...` (2025-01-14)
State: closed | Pull request: yes
Labels: name: Run CICD

🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=64862035dbb9b03f40b09cfe26b82306609f7153`.  

📝 Please remember the following to-do's before merge: 
- [ ] Verify the presubmit CI  

🙏 Please merge this PR only if the CI workflow completed successfully.
Add qwen trtllm
State: open | Pull request: yes

# What does this PR do ?

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
# Add a code snippet demonstrating how to use this 
```

# GitHub Actions CI

The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.

The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Failing convert_llama_hf_to_nemo.py
State: open | Pull request: no
Labels: name: bug

**Failing convert_llama_hf_to_nemo.py**

Running `convert_llama_hf_to_nemo.py` fails with an error `TypeError: expected string or bytes-like object` when trying to execute `python /home/ubuntu/NeMo/scripts/checkpoint_converters/convert_llama_hf_to_nemo.py     --input_name_or_path meta-llama/Llama-3.2-1B-Instruct     --output_path Llama-3.2-1B.nemo`

**Steps/Code to reproduce bug**

When running `python /home/ubuntu/NeMo/scripts/checkpoint_converters/convert_llama_hf_to_nemo.py     --input_name_or_path meta-llama/Llama-3.2-1B-Instruct     --output_path Llama-3.2-1B.nemo` I get the following error.

```bash

Traceback (most recent call last):
  File "/home/ubuntu/NeMo/scripts/checkpoint_converters/convert_llama_hf_to_nemo.py", line 344, in <module>
    convert(args)
  File "/home/ubuntu/NeMo/scripts/checkpoint_converters/convert_llama_hf_to_nemo.py", line 310, in convert
    model = load_state_dict_helper(MegatronGPTModel, nemo_config, trainer, checkpoint['state_dict'])
  File "/home/ubuntu/miniconda3/envs/nemo/lib/python3.10/site-packages/nemo/collections/nlp/parts/utils_funcs.py", line 220, in load_state_dict_helper
    model = cls(cfg, trainer)
  File "/home/ubuntu/miniconda3/envs/nemo/lib/python3.10/site-packages/nemo/collections/nlp/models/language_modeling/megatron_gpt_model.py", line 331, in __init__
    super().__init__(cfg, trainer=trainer, no_lm_init=True)
  File "/home/ubuntu/miniconda3/envs/nemo/lib/python3.10/site-packages/nemo/collections/nlp/models/language_modeling/megatron_base_model.py", line 153, in __init__
    self._enable_nvidia_optimizations()
  File "/home/ubuntu/miniconda3/envs/nemo/lib/python3.10/site-packages/nemo/collections/nlp/models/language_modeling/megatron_base_model.py", line 393, in _enable_nvidia_optimizations
    if not is_official_release_version(nvidia_torch_version):
  File "/home/ubuntu/miniconda3/envs/nemo/lib/python3.10/site-packages/nemo/collections/nlp/models/language_modeling/megatron_base_model.py", line 390, in is_official_release_version
    return re.fullmatch("[0-9][0-9]\.[0-9][0-9].*", nvidia_torch_version)  # "YY.MM.*"
  File "/home/ubuntu/miniconda3/envs/nemo/lib/python3.10/re.py", line 195, in fullmatch
    return _compile(pattern, flags).fullmatch(string)
TypeError: expected string or bytes-like object
```

**Environment overview **

 - Environment location: Cloud(Lambdalabs)
 - Method of NeMo install: from srouce using `python -m pip install git+https://github.com/NVIDIA/NeMo.git@r2.1.1#egg=nemo_toolkit[all]`

**Environment details**
- OS version: Debian
- PyTorch version: 2.4.1+cu124
- Python version: Python 3.10

**Additional context**
GPU model: `A100`