ckpt to nemo or model about nemo

[taras-sereda]

Hi for these proposes I wrote a tiny script for my ASR models, that accepts .ckpt model and saves it as .nemo model

I think something similar should work for NLP models too.

import sys
from pathlib import Path

import nemo.collections.asr as nemo_asr


def get_nemo_ckpt_path(ckpt_path: Path) -> Path:
    ckpt_name = ckpt_path.stem
    name, other = ckpt_name.split("--")
    epoch = other.split("=")[-1]
    out_path = ckpt_path.with_name(f"{name}-epoch-{epoch}.nemo")
    return out_path

def export_to_nemo(lightning_ckpt_path: Path):
    model = nemo_asr.models.EncDecCTCModelBPE.load_from_checkpoint(
        str(lightning_ckpt_path)
    )
    ckpt_name = get_nemo_ckpt_path(lightning_ckpt_path)
    out_path = get_nemo_ckpt_path(lightning_ckpt_path)
    model.save_to(str(out_path))
    print(f"Succesfully saved model checkpoint: {out_path} in nemo format")


if __name__ == "__main__":
    in_path = Path(sys.argv[1])
    assert in_path.exists()
    export_to_nemo(in_path)

[gslin1224]

Hi for these proposes I wrote a tiny script for my ASR models, that accepts .ckpt model and saves it as .nemo model

I think something similar should work for NLP models too.

import sys
from pathlib import Path

import nemo.collections.asr as nemo_asr


def get_nemo_ckpt_path(ckpt_path: Path) -> Path:
    ckpt_name = ckpt_path.stem
    name, other = ckpt_name.split("--")
    epoch = other.split("=")[-1]
    out_path = ckpt_path.with_name(f"{name}-epoch-{epoch}.nemo")
    return out_path

def export_to_nemo(lightning_ckpt_path: Path):
    model = nemo_asr.models.EncDecCTCModelBPE.load_from_checkpoint(
        str(lightning_ckpt_path)
    )
    ckpt_name = get_nemo_ckpt_path(lightning_ckpt_path)
    out_path = get_nemo_ckpt_path(lightning_ckpt_path)
    model.save_to(str(out_path))
    print(f"Succesfully saved model checkpoint: {out_path} in nemo format")


if __name__ == "__main__":
    in_path = Path(sys.argv[1])
    assert in_path.exists()
    export_to_nemo(in_path)

Thanks for your reply.

It seems like changing the import nemo.collections.asr as nemo_asr might work.

Have you tried converting the Nemo format to gguf? Alternatively, how do you build a model from your Nemo format?

Thank you.