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")# 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 pytorch_model.bin from Aanchan/psst_model_cer_2: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/Aanchan/psst_model_cer_2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Aanchan/psst_model_cer_2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Aanchan/psst_model_cer_2/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 97200e2c45b79469b7ccdccb066678deb59453da4e1dfb113607d00f316f58fe
- Size of remote file:
- 378 MB
- SHA256:
- a7fd5d234c1448d358c185571f95164ae62c29ce8493347c477df4a11325db8b
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