Instructions to use Siyong/M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Siyong/M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Siyong/M")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Siyong/M") model = AutoModelForCTC.from_pretrained("Siyong/M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Siyong/M: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/Siyong/M/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Siyong/M/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Siyong/M/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 9b66b875d7ade2dcd4e069a7d3ebfad49de3e003a9880b9192c9c8c4e609dfc0
- Size of remote file:
- 378 MB
- SHA256:
- 44df88d5520f8049f1cb1583cce52cd79bb32928b6ff0b044365f98baba5a2e2
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