Automatic Speech Recognition
Transformers
PyTorch
Hausa
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 Akashpb13/Hausa_xlsr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akashpb13/Hausa_xlsr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Akashpb13/Hausa_xlsr")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Akashpb13/Hausa_xlsr") model = AutoModelForCTC.from_pretrained("Akashpb13/Hausa_xlsr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Akashpb13/Hausa_xlsr: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/Akashpb13/Hausa_xlsr/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Akashpb13/Hausa_xlsr/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Akashpb13/Hausa_xlsr/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- e0cfb694094893408fdc5c63d40659f6c7f894ac073f53c49b6895ea6fe7c979
- Size of remote file:
- 1.26 GB
- SHA256:
- 7be87e0d4d5617e9068e57ef8f6b00e4cb98c93ac21b4ed18d1cc7d5570872e0
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