Instructions to use Sjdan/f05_main with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/f05_main with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/f05_main")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/f05_main") model = AutoModelForCTC.from_pretrained("Sjdan/f05_main", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Sjdan/f05_main: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/Sjdan/f05_main/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Sjdan/f05_main@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sjdan/f05_main/resolve/refs%2Fpr%2F1/pytorch_model.bin
1.26 GB
- Xet hash:
- abdf4a8cd0ce313810dca933c73b7351901e8e0eb411c89ea3d6533ee8403fe4
- Size of remote file:
- 1.26 GB
- SHA256:
- 939dcc5cf27a8fb4513f0bd39b0e479f38e51af5921e01f6accf6576ed2cd591
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