Automatic Speech Recognition
NeMo
Finnish
asr
speech-recognition
canary-v2
kenlm
finnish
Eval Results (legacy)
Instructions to use RASMUS/Finnish-ASR-Canary-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use RASMUS/Finnish-ASR-Canary-v2 with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("RASMUS/Finnish-ASR-Canary-v2") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
| # Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| from lightning.pytorch.callbacks import Callback as PTLCallback | |
| class BaseCallback(PTLCallback): | |
| """Base callback ABC for NeMo lifecycle hooks (extends PTL callback). | |
| Implementers may override any subset of the following methods. All are | |
| optional no-op defaults to keep implementations lightweight. | |
| """ | |
| # App lifecycle | |
| def on_app_start(self, *args, **kwargs) -> None: | |
| """Called when the application starts.""" | |
| pass | |
| def on_app_end(self, *args, **kwargs) -> None: | |
| """Called when the application ends.""" | |
| pass | |
| # Model lifecycle | |
| def on_model_init_start(self, *args, **kwargs) -> None: | |
| """Called when model initialization starts.""" | |
| pass | |
| def on_model_init_end(self, *args, **kwargs) -> None: | |
| """Called when model initialization ends.""" | |
| pass | |
| # Dataloader lifecycle | |
| def on_dataloader_init_start(self, *args, **kwargs) -> None: | |
| """Called when dataloader initialization starts.""" | |
| pass | |
| def on_dataloader_init_end(self, *args, **kwargs) -> None: | |
| """Called when dataloader initialization ends.""" | |
| pass | |
| # Optimizer lifecycle | |
| def on_optimizer_init_start(self, *args, **kwargs) -> None: | |
| """Called when optimizer initialization starts.""" | |
| pass | |
| def on_optimizer_init_end(self, *args, **kwargs) -> None: | |
| """Called when optimizer initialization ends.""" | |
| pass | |
| # Checkpoint lifecycle | |
| def on_load_checkpoint_start(self, *args, **kwargs) -> None: | |
| """Called when checkpoint loading starts.""" | |
| pass | |
| def on_load_checkpoint_end(self, *args, **kwargs) -> None: | |
| """Called when checkpoint loading ends.""" | |
| pass | |
| def on_save_checkpoint_start(self, *args, **kwargs) -> None: | |
| """Called when checkpoint saving starts.""" | |
| pass | |
| def on_save_checkpoint_end(self, *args, **kwargs) -> None: | |
| """Called when checkpoint saving ends.""" | |
| pass | |
| def on_save_checkpoint_success(self, *args, **kwargs) -> None: | |
| """Called when checkpoint saving succeeds.""" | |
| pass | |
| # Configuration update | |
| def update_config(self, *args, **kwargs) -> None: | |
| """Update callback-specific configuration after initialization.""" | |
| pass | |
| __all__ = ["BaseCallback"] | |