Instructions to use Sjdan/f03_main with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/f03_main with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/f03_main")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/f03_main") model = AutoModelForCTC.from_pretrained("Sjdan/f03_main", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Sjdan/f03_main: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/Sjdan/f03_main/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Sjdan/f03_main@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sjdan/f03_main/resolve/refs%2Fpr%2F1/pytorch_model.bin
1.26 GB
- Xet hash:
- 8e76af239c45553609477786535b620a1cbb8bb0f34878e8b6d78afbef4a2bed
- Size of remote file:
- 1.26 GB
- SHA256:
- 06f1641cca6fd07b65e821cbfa893b45baf07190eb5bda0f23dc739560a585f3
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