Automatic Speech Recognition
Transformers
PyTorch
JAX
Italian
wav2vec2
audio
speech
apache-2.0
portuguese-speech-corpus
xlsr-fine-tuning-week
PyTorch
Eval Results (legacy)
Instructions to use joaoalvarenga/wav2vec2-large-xlsr-italian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joaoalvarenga/wav2vec2-large-xlsr-italian with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="joaoalvarenga/wav2vec2-large-xlsr-italian")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("joaoalvarenga/wav2vec2-large-xlsr-italian") model = AutoModelForCTC.from_pretrained("joaoalvarenga/wav2vec2-large-xlsr-italian", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8247432dbf3b4a1e1057c0790aef42d59bee33afb4475df4601e71f887d1d0a
- Size of remote file:
- 1.26 GB
- SHA256:
- 1e1325e6e6dca4a5fa6e6a615c0fc13bf0015eb0675476a0c8be7b79163ab359
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.