Fail to convert Llama3 Nemo 2.0 checkpoint to HF

[EthanLI24]

Describe the bug

I use Nemo 2.0 to train my model and get Nemo 2.0 checkpoint like this with .distcp files:
model_name
├── context
│ ├── model_config.yaml
│ ├── io.json
│ └── tokenizer
├── weights
│ ├── distributed checkpointing directories/files in torch_dist format
│ ├── metadata.json
│ └── common.pt

but filed to use NeMo/scripts/checkpoint_converters/convert_llama_nemo_to_hf.py to export it to a HF file

Expected behavior

get HF files by Nemo2.0 checkpoint

[EthanLI24]

Is there a way we can now save non .distcp files or huggingface .bin files directly after training?
If not, how to convert nemo2.0 checkpoint to the community common format?

[hemildesai]

Hi, the scripts/checkpoint_converters/convert_llama_nemo_to_hf.py script is only for NeMo 1.0 checkpoints. To export 2.0 checkpoints, you can use a custom script like

from pathlib import Path

from nemo.collections.llm import export_ckpt

if __name__ == "__main__":
    export_ckpt(
        path=Path("/workspace/input_ckpt"),
        target="hf",
        output_path=Path("/workspace/output_ckpt.hf"),
    )

[EthanLI24]

Hi, the scripts/checkpoint_converters/convert_llama_nemo_to_hf.py script is only for NeMo 1.0 checkpoints. To export 2.0 checkpoints, you can use a custom script like

from pathlib import Path

from nemo.collections.llm import export_ckpt

if name == "main":
export_ckpt(
path=Path("/workspace/input_ckpt"),
target="hf",
output_path=Path("/workspace/output_ckpt.hf"),
)

Here are my fold arch:

nemo2_llama3
├── context
│ ├── model.yaml
│ ├── io.json
│ └── nemo_tokenizer
├── weights
│ ├── __0_0.distcp
│ ├── __0_1.distcp
│ ├── metadata.json
│ └── common.pt

and I follow your instruction to use

if __name__ == "__main__":
    export_ckpt(
        path=Path("./nemo2_llama3"),
        target="hf",
        output_path=Path("./nemo2exporthf"),
    )

but i get failed again, could you help me with this?