Instructions to use AK-12/my_asr_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AK-12/my_asr_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="AK-12/my_asr_2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("AK-12/my_asr_2") model = AutoModelForSpeechSeq2Seq.from_pretrained("AK-12/my_asr_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AK-12/my_asr_2: direct link, hf CLI and curl.
- Browser
- Download file 4.22 kB
-
https://huggingface.co/AK-12/my_asr_2/resolve/main/training_args.bin
- Command line
-
hf download hf://AK-12/my_asr_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AK-12/my_asr_2/resolve/main/training_args.bin
4.22 kB
- Xet hash:
- 43d8b7ab4625f89e143258c81677673a26ee88f4a371221b41fb25b0605cb976
- Size of remote file:
- 4.22 kB
- SHA256:
- 784495c36a32b59cff82f94c08e05b2555ddbea92546cd3bf144590b6d306908
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