Instructions to use rms7988/ASR-AFRI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rms7988/ASR-AFRI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rms7988/ASR-AFRI")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("rms7988/ASR-AFRI") model = AutoModelForSpeechSeq2Seq.from_pretrained("rms7988/ASR-AFRI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rms7988/ASR-AFRI: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/rms7988/ASR-AFRI/resolve/main/training_args.bin
- Command line
-
hf download hf://rms7988/ASR-AFRI/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rms7988/ASR-AFRI/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 34c02d50baa3f829af75a7feb07ed019b38edbc1695647deabcdb7cddc73c57e
- Size of remote file:
- 5.24 kB
- SHA256:
- 52a2239288b000a4c7c4d3611a8c3c10e97c83999a47900623c60c123203bd03
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