Instructions to use Vkt/model-facebookptbrlarge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vkt/model-facebookptbrlarge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Vkt/model-facebookptbrlarge")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Vkt/model-facebookptbrlarge") model = AutoModelForCTC.from_pretrained("Vkt/model-facebookptbrlarge", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Vkt/model-facebookptbrlarge: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/Vkt/model-facebookptbrlarge/resolve/main/training_args.bin
- Command line
-
hf download hf://Vkt/model-facebookptbrlarge/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Vkt/model-facebookptbrlarge/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 3d001f36f4c004885c0d179b5b445b6823af863dc3449854b153dc96056271df
- Size of remote file:
- 3.06 kB
- SHA256:
- 3734220d89b08dca5b7c7f074b5a49d6886204dfe66c8f66d9349a39a67c8c16
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