Instructions to use AlexanderMaz/LanguageModel_Fusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use AlexanderMaz/LanguageModel_Fusion with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("AlexanderMaz/LanguageModel_Fusion") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
Commit History
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Upload data
1. Trained word-level LSTM. 2. Trained token-level 4-gram arpa model. 3. Fine-tuned gpt2 model. 4. Baseline ASR model (https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_en_conformer_transducer_small). 5. LibriSpeech text data for train, validation and test.36c6e03