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Changes:
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2. switch from dropout 0 to 0.1
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# What does this PR do ?
Allows to use cached models without internet connection
**Collection**: [Note which collection this PR will affect]
# Changelog
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trainer.max_steps=-1 \
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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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Add a one line overview of what this PR aims to accomplish.
**Collection**: LLM
# Changelog
- Introduce standardized API dataclasses for evals configuration
- Modify the evaluate method to comply with the new format
# Usage
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import os
import nemo_run as run
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```
# It contains the default values for training a Fast Conformer-CTC ASR model, large size (~120M) with CTC loss and sub-word encoding.
# This version uses Longformer-style attention in order to handle longer audio
# You may find more detail:
# FastC... | null | {
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# Usage
* You can potentially add a usage example below
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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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# Usage
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`_find_trainer_ckpt_path` crashes if it restores from an imported ckpt with a restore config.
**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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**Collection**: [Note which collection this PR will affect]
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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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**PR Type**:
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**Collection**: [Note which collection this PR will affect]
# Changelog
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# Usage
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add expert tensor parallelism support for NeMo2.0 MoE and substitute get_data_modulo_expert_parallel_group with get_expert_data_parallel_group since the former one is going to be deprecated.
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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 ?
Disable tests that download datasets from the web to avoid unstable tests (e.g. remote host goes down).
TODO: store dataset locally.
**Collection**: [Note which collection this PR will affect]
# Changelog
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* You can potentially add a usage example below
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"> Is this a safe hacking? wouldn't this impact functionality if you override `cu_seqlens_unpadded`?\r\n\r\nTested in the case of CP=1 this is fine. Not confident about CP>1. Do you have suggestions on how to tac... | 2025-01-16T17:58:44 | 2025-01-18T11:44:07 | null | COLLABORATOR | {
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Adds a te version guard for packed sequence in NeMo 1 (NeMo 2 is unaffected)
Changes in #10688 should be paired with TE version >1.3
https://github.com/NVIDIA/TransformerEngine/blob/3d63cbb469ace2d1ad7798a956e16dee42bd655b/transformer_engine/pytorch/attention.py#L8179-L8185
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# Usage
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Traceback (most recent call last):
File "/user/panyinxu/workspace/NeMo-Aligner/examples/nlp/minicpm/train_minicpm3_4b_longrope_dpo.py", line 164, in <module>
main()
File "/user/panyinxu/workspace/NeMo/nemo/core/config/hydra_runner.py", line 129, in wrapper
_run_hydra(
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**Collection**: NLP
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* You can potentially add a usage example below
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# Add a code snippet demonstrating how to use this
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📝 Please remember the following to-do's before merge:
- [ ] Verify the presubmit CI
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>GPU LLM test failing: It clearly started only today. And that PR 10693 had a really old CI signal (it was a week old). So quite likely that a re-run of the CI would have failed. But since we don’t require up-to-date CI, it got merged | null | {
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`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 tim... | {
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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
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Removes the pin from tensorstore 0.1.45 from requirements_deploy.txt, since the issue was fixed in 0.1.47.
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} | 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 ?
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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.
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A simple fix for the Qwen2 importer:
Qwen2 7B and larger require `vocab_size=152064` instead of default `vocab_size=151936`. The `HFQwen2Importer.config` missed this setting.
**Collection**: `llm`
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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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"@zpx01 can you take a look?",
"@Sy-Zhang can you try changing the following line:\nhttps://github.com/NVIDIA/NeMo/blob/1626ddded63af1fe82b0bee482fba44c57b8203d/nemo/collections/common/video_tokenizers/cosmos_tokenizer.py#L205\n\nto this:\n\n`output_tensor = self.encode(input_tensor)`\n\nI think this will tempora... | 2025-01-14T22:01:10 | 2025-01-16T05:51:21 | null | NONE | {
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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/dif... | null | {
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"<!-- pylint-output-strict-mode-false -->\n\nbeep boop 🤖: 🙏 The following files have warnings. In case you are familiar with these, please try helping us to improve the code base.\n\n---\n\nYour code was analyzed with PyLint. The following annotations have been identified:\n\n```\n************* Module nemo.collec... | 2025-01-14T21:42:57 | 2025-01-15T07:01:33 | null | NONE | {
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* Command: `torchrun --nproc-per-node 8 nemo/collections/diffusion/train.py --yes --factory pretrain_xl`
* Error: `CrossAttentionSubmodules.__init__() got an unexpected keyword argument q_layernorm`
* Reason: `megatron.core.transformer.attention.CrossAttentionSubmodu... | null | {
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"<!-- pylint-output-strict-mode-true -->\n\nbeep boop 🤖: 🚨 The following files must be fixed before merge!\n\n---\n\nYour code was analyzed with PyLint. The following annotations have been identified:\n\n```\n************* Module nemo.collections.vlm.vision.base\nnemo/collections/vlm/vision/base.py:38:0: C0116: M... | 2025-01-14T19:57:35 | 2025-01-15T21:28:42 | null | COLLABORATOR | {
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Refactor VLM modules / Add InternVit submodule support
**Collection**: [multimodal / 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... | null | {
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Add CP support to Neva in NeMo2.
**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 ... | null | {
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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 \
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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... | null | {
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} | # 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
`... | null | {
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1) Handles trt-llm export for fp8 NeMo 2.0 checkpoints, trained with TransformerEngine
2) Handles fp8 parameters for NeMo 1.0 -> NeMo 2.0 conversion
**Collection**: nlp/llm
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentia... | null | {
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📝 Please remember the following to-do's before merge:
- [ ] Verify the presubmit CI
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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
```python
# Add a cod... | null | {
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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 --... | null | {
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Uses sentence-piece legacy to handle special tokens as part of text, this change only affects mistralai/Mistral-7B-Instruct-v0.3
**Collection**: [Note which collection this PR will affect]
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"I found the issue. Instead of installing from `main` branch, it wokred when I reinstall from `r2.*`"
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I am getting `ModuleNotFoundError: No module named 'megatron.core.dist_checkpointing'`
**Steps/Code to reproduce bug**
```bash
python /home/ubuntu/NeMo/scripts/checkpoint_converters/convert_llama_hf_to_nemo.py --input_name_or_path meta-l... | {
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**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.
# Usage
* You can potentially add a usage example below
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https://api.github.com/repos/NVIDIA/NeMo/issues/11836 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/11836/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/11836/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/11836/events | https://github.com/NVIDIA/NeMo/issues/11836 | 2,784,367,262 | I_kwDOC_bI7s6l9hKe | 11,836 | Creating a hf to nemo converter for phi 3 mini instruct | {
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"@LopezGG the Phi3 mini has already been added [here](https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/llm/gpt/model/phi3mini.py). The steps to do the fine-tuning with Phi3 are also described in the recipe as [well](https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/llm/recipes/phi3_mini_4k_instruc... | 2025-01-13T15:36:11 | 2025-01-14T17:42:46 | 2025-01-14T06:08:53 | NONE | {
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I am following the guidelines https://docs.nvidia.com/nemo-framework/user-guide/latest/nemotoolkit/checkpoints/dev_guide.html to create a converter. It looks like in addition to qkv reshaping and layer name mapping we need to load phi model into megatron_gpt_model. @cuichenx and @mayani-nv I noticed you have some... | {
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You try to install NeMo then mamba-ssm fails, you spend another 3 hrs trying to resolve it, you give... | {
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} | # What does this PR do ?
Reuse `_get_mlp_module_spec ` from Megatron Core to improve stability. This also fixes Mixtral loading bug as the current implementation fails with:
```
File "/opt/megatron-lm/megatron/core/transformer/moe/moe_layer.py", line 109, in __init__
self.experts = build_module(self.submodu... | {
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} | # What does this PR do ?
See https://github.com/NVIDIA/NeMo/pull/11820
**Collection**: NLP / LLM
# 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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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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} | 🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=c76410adec0eb1f81544344fcc2c404166e9913d`.
📝 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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"<!-- pylint-output-strict-mode-false -->\n\nbeep boop 🤖: 🙏 The following files have warnings. In case you are familiar with these, please try helping us to improve the code base.\n\n---\n\nYour code was analyzed with PyLint. The following annotations have been identified:\n\n```\n************* Module nemo.collec... | 2025-01-12T19:48:51 | 2025-01-13T18:14:16 | 2025-01-13T18:14:14 | COLLABORATOR | {
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Fix how we calculate the num_available_samples for the case of training more than one epoch on the line:
https://github.com/NVIDIA/NeMo/blob/7f3ac6b88289048643d445ec752a4d21547f2788/nemo/collections/nlp/data/language_modeling/megatron/megatron_batch_samplers.py#L129
When interrupting the ... | {
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} | # What does this PR do ?
Fix the error when running llama3 and llama31 peft with nemo2 local job.
**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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} | null | null | null | The reproduction steps and detailed information have been documented on the Megatron-LM side.
I will open the same issue on the NeMo side.
https://github.com/NVIDIA/Megatron-LM/issues/1350
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https://api.github.com/repos/NVIDIA/NeMo/issues/11827 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/11827/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/11827/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/11827/events | https://github.com/NVIDIA/NeMo/pull/11827 | 2,782,206,166 | PR_kwDOC_bI7s6HcLg8 | 11,827 | chore(beep boop 🤖): Bump `MCORE_TAG=726da58...` (2025-01-12) | {
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} | 🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=726da588ead74ac7f5e62324dea478c1dabb4150`.
📝 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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https://api.github.com/repos/NVIDIA/NeMo/issues/11826 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/11826/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/11826/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/11826/events | https://github.com/NVIDIA/NeMo/issues/11826 | 2,782,047,331 | I_kwDOC_bI7s6l0qxj | 11,826 | Canary ouputs English for Arabic Speech | {
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"@BenoitWang Can you try `ar-SA`? We may have just assigned Arabic language under a Saudi dialect tag for that round.",
"Hi @tbartley94, just tried but still got English outputs.",
"hmm, okay will look into it",
"@BenoitWang It looks like you're using Riva client to run Canary-1b model. If so, you need to pas... | 2025-01-11T18:05:15 | 2025-01-16T18:54:09 | null | NONE | {
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Hello, I am trying to infer [Canary 1b](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/riva/models/canary-riva-1b) for Arabic ASR with Riva quick start 2.18.0. According to the description it has already supported Arabic, but it outputs English instead of Arabic tokens.
Here's a partial extrac... | null | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/11825 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/11825/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/11825/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/11825/events | https://github.com/NVIDIA/NeMo/issues/11825 | 2,781,946,312 | I_kwDOC_bI7s6l0SHI | 11,825 | when i use container to do sft for any model, it has context not found error | {
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"09-53\ni.finetune/0 GPU available: True (cuda), used: True\ni.finetune/0 TPU available: False, using: 0 TPU cores\ni.finetune/0 HPU available: False, using: 0 HPUs\ni.finetune/0 [NeMo W 2025-01-11 15:09:53 nemo_logger:173] \"update_logger_directory\" is True. Overwriting tensorboard logger \"save_dir\" to tb_logs\... | 2025-01-11T15:05:52 | 2025-01-11T15:10:54 | null | NONE | {
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} | null | null | null | container docker pull nvcr.io/nvidia/nemo:24.12
nemo llm finetune -f llama32_1b peft=lora # acceptable values are lora/dora/none
it has error like No such file: '/root/.cache/nemo/models/meta-llama/Llama-3.2-1B/context'
the document i followed
https://docs.nvidia.com/nemo-framework/user-guide/latest/sft_peft/p... | null | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/11824 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/11824/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/11824/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/11824/events | https://github.com/NVIDIA/NeMo/issues/11824 | 2,781,772,516 | I_kwDOC_bI7s6lznrk | 11,824 | How to use nemo docker container as base image | {
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"@wheynelau thanks for your reply.\nThat is what I'm doing. Here is my dockerfile:\n\n```dorckerfile\nFROM nvcr.io/nvidia/nemo:24.12 AS base\nEXPOSE 8080\n\n# Install PowerShell ... | 2025-01-11T11:27:30 | 2025-01-13T08:55:22 | null | NONE | {
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I'm trying to create a docker image that uses nemo as the base image.
I have a python project with some scripts (including a requirements.txt file with some additional dependencies) that I'm containerizing on that same image.
The Nemo base image is around 29GB in size but when I run pip install on the requirements... | null | {
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"<!-- pylint-output-strict-mode-false -->\n\nbeep boop 🤖: 🙏 The following files have warnings. In case you are familiar with these, please try helping us to improve the code base.\n\n---\n\nYour code was analyzed with PyLint. The following annotations have been identified:\n\n```\n************* Module nemo.collec... | 2025-01-11T01:39:33 | 2025-01-16T16:50:56 | null | COLLABORATOR | {
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The only config not preserved is max_position_embeddings since we lose that information b/c nemo uses `seq_length`. Even though the original value would be lost during an `export(import(ckpt))` conversion, it's probably a confusing UX if we allow this to be configurable upon export since mos... | null | {
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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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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 cod... | null | {
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} | # What does this PR do ?
Gets the value of `generation_logits_available` from `inputs["output_generation_logits"][0][0]` so that it is a bool as opposed to `inputs["output_generation_logits"]` where it's a np array and can give error when the array is len > 1.
**Collection**: [Note which collection this PR will a... | {
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we've cherry picked #11788 into for you! 🚀
Please review and approve this cherry pick by your convenience! | {
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This PR is making Some of ASR models outputs consistent
**Collection**: ASR
# 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 ... | null | {
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There are two places in the document (as shown in the following) that mention the performance improvement of sequence packing, but the data differs greatly.
10x performance improvement is unthinkable. **_Is it a typo?_**
https://docs.nvidia.com/nemo-framework/user-guide/lat... | null | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/11813 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/11813/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/11813/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/11813/events | https://github.com/NVIDIA/NeMo/issues/11813 | 2,779,509,479 | I_kwDOC_bI7s6lq_Ln | 11,813 | ASR: Is there any checked and stable way for pretrain? | {
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"No one knows pretrain mechanism???\nIt is so-so strange "
] | 2025-01-10T07:45:16 | 2025-01-15T04:27:27 | null | NONE | {
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I am trying to develop ASR tools for 2 custom languages.
I used 3-4 times speech_to_text_ctc_bpe.py for pretrain, but all cases I did not receive reslult. My best results is WER:0.98.
```
python speech_to_text_ctc_bpe.py \
+config-name=../conf/fastconformer/fast-conformer_ctc_bpe \
model.train_ds.manifest_... | null | {
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yaml set noise:
```
model:
train_ds:
augmentor:
time_stretch:
.....
gain:
......
noise:
manifest_path: background_noise.json
.....
white_noise:
......
```
How should I set it when u... | null | {
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} | # What does this PR do ?
Changes:
1. previously, it was inserting a space token between the a special token and the first word of the text following the special token.
2. apply the above to text_to_tokens and text_to_ids
3. if a special token is in the vocab, then use its id when marking it as special token.
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Update the readme for news about Cosmos WFMs.
**Collection**: readme
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**Collection**: readme
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