Instructions to use NathanRoll/psst-medium-en-q with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NathanRoll/psst-medium-en-q with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NathanRoll/psst-medium-en-q")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NathanRoll/psst-medium-en-q") model = AutoModelForSpeechSeq2Seq.from_pretrained("NathanRoll/psst-medium-en-q", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download decoder_model_quantized.onnx from NathanRoll/psst-medium-en-q: direct link, hf CLI and curl.
- Browser
- Download file 514 MB
-
https://huggingface.co/NathanRoll/psst-medium-en-q/resolve/main/decoder_model_quantized.onnx
- Command line
-
hf download hf://NathanRoll/psst-medium-en-q/decoder_model_quantized.onnx
-
curl -L -o decoder_model_quantized.onnx https://huggingface.co/NathanRoll/psst-medium-en-q/resolve/main/decoder_model_quantized.onnx
514 MB
- Xet hash:
- 566e1333d641675660fbd51fbd7d372847d88cb4c7df17bed1d4793f27fcf40d
- Size of remote file:
- 514 MB
- SHA256:
- b12862ff2dd9ef5c9bd549a2762877c07857083e3242b41011e730c8f6a156c8
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