Automatic Speech Recognition
Transformers
PyTorch
Slovenian
wav2vec2
Generated from Trainer
hf-asr-leaderboard
model_for_talk
mozilla-foundation/common_voice_8_0
robust-speech-event
Eval Results (legacy)
Instructions to use DrishtiSharma/wav2vec2-large-xls-r-300m-sl-with-LM-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DrishtiSharma/wav2vec2-large-xls-r-300m-sl-with-LM-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DrishtiSharma/wav2vec2-large-xls-r-300m-sl-with-LM-v1")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-sl-with-LM-v1") model = AutoModelForCTC.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-sl-with-LM-v1") - Notebooks
- Google Colab
- Kaggle
File size: 196 Bytes
3579ac6 | 1 2 3 4 5 6 7 8 | {
"epoch": 100.0,
"train_loss": 1.2146642443028892,
"train_runtime": 11060.029,
"train_samples": 2606,
"train_samples_per_second": 23.562,
"train_steps_per_second": 0.741
} |