Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
wav2vec2
google/fleurs
Generated from Trainer
pashto
ps
Eval Results (legacy)
Instructions to use ihanif/wav2vec2-xls-r-300m-pashto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ihanif/wav2vec2-xls-r-300m-pashto with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ihanif/wav2vec2-xls-r-300m-pashto")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ihanif/wav2vec2-xls-r-300m-pashto") model = AutoModelForCTC.from_pretrained("ihanif/wav2vec2-xls-r-300m-pashto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63b61ddf07a265da4a4d9591758317883a196677e4ae009bbf646e6042277fa9
- Size of remote file:
- 1.26 GB
- SHA256:
- 6652626725a3eddd49ea792e6835d71505cc84a0fb7477beeb1b26c06c99c39b
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