Instructions to use Sjdan/f03 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/f03 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/f03")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/f03") model = AutoModelForCTC.from_pretrained("Sjdan/f03", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Sjdan/f03: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/Sjdan/f03/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Sjdan/f03/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sjdan/f03/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- efd72bb0418c938ee9c00e27b8250e7a3db542fcb413f474a8b8930699178573
- Size of remote file:
- 1.26 GB
- SHA256:
- 18fc13a190d5af73ed0d2bec115fdc9f3cfa87da9ebfb87511cbe75c2141f05c
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