Instructions to use Aanchan/psst_model_cer_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aanchan/psst_model_cer_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Aanchan/psst_model_cer_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Aanchan/psst_model_cer_2") model = AutoModelForCTC.from_pretrained("Aanchan/psst_model_cer_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Aanchan/psst_model_cer_2: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/Aanchan/psst_model_cer_2/resolve/main/training_args.bin
- Command line
-
hf download hf://Aanchan/psst_model_cer_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Aanchan/psst_model_cer_2/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 99da71e43a9178026b5cc92889d7e4a47e50b7f0deb06b89cf8ba20a9016ce9e
- Size of remote file:
- 3.52 kB
- SHA256:
- e90baf5d2d9945d87e4dffde5b28f54e5d008a41d81777afd659e1515c1d3dfe
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