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 encoder_model_quantized.onnx from NathanRoll/psst-medium-en-q: direct link, hf CLI and curl.
- Browser
- Download file 313 MB
-
https://huggingface.co/NathanRoll/psst-medium-en-q/resolve/main/encoder_model_quantized.onnx
- Command line
-
hf download hf://NathanRoll/psst-medium-en-q/encoder_model_quantized.onnx
-
curl -L -o encoder_model_quantized.onnx https://huggingface.co/NathanRoll/psst-medium-en-q/resolve/main/encoder_model_quantized.onnx
313 MB
- Xet hash:
- ff899e64a9277f9fa88804368fd1b7f4d1d5d7805fe4d005ea525e1f81ef2142
- Size of remote file:
- 313 MB
- SHA256:
- a553c69e2caaec2f4f1767374ad554a483223ffe8e8bea1112b224a3a7a05952
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