Instructions to use Abkrs1/Hausa-ASR-copy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abkrs1/Hausa-ASR-copy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Abkrs1/Hausa-ASR-copy")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Abkrs1/Hausa-ASR-copy") model = AutoModelForSpeechSeq2Seq.from_pretrained("Abkrs1/Hausa-ASR-copy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Abkrs1/Hausa-ASR-copy: direct link, hf CLI and curl.
- Browser
- Download file 967 MB
-
https://huggingface.co/Abkrs1/Hausa-ASR-copy/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Abkrs1/Hausa-ASR-copy/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Abkrs1/Hausa-ASR-copy/resolve/main/pytorch_model.bin
967 MB
- Xet hash:
- 9fcebbc454f0f6a171a6f6acff2f02fbb375384f6e4c8bdb62309e5b5bd01f6d
- Size of remote file:
- 967 MB
- SHA256:
- edc2d0b56a6861436bdbc066edb961d093684824145f9cb621e697b2b5c0ff98
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