Instructions to use Sjdan/m16_main with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/m16_main with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/m16_main")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/m16_main") model = AutoModelForCTC.from_pretrained("Sjdan/m16_main", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Sjdan/m16_main: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/Sjdan/m16_main/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Sjdan/m16_main@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sjdan/m16_main/resolve/refs%2Fpr%2F1/pytorch_model.bin
1.26 GB
- Xet hash:
- 02ed8150e4a58d495c6db74f55cf348f46b60a1f312c2f1cb090299f44e86cba
- Size of remote file:
- 1.26 GB
- SHA256:
- 068663e21aad36df18777d35c2c248229188b9b39044498b7d2e4f1352634bd2
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