Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Vietnamese
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use joey234/whisper-medium-vi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joey234/whisper-medium-vi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="joey234/whisper-medium-vi")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("joey234/whisper-medium-vi") model = AutoModelForSpeechSeq2Seq.from_pretrained("joey234/whisper-medium-vi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from joey234/whisper-medium-vi: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/joey234/whisper-medium-vi/resolve/378e049b5b3bbe7371532bb4a531583a4572f4b5/training_args.bin
- Command line
-
hf download hf://joey234/whisper-medium-vi@378e049b5b3bbe7371532bb4a531583a4572f4b5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/joey234/whisper-medium-vi/resolve/378e049b5b3bbe7371532bb4a531583a4572f4b5/training_args.bin
3.52 kB
- Xet hash:
- 6aacd64d05eda997722f002d71885727dddfbab5c79f4d43824b7cffef0b8942
- Size of remote file:
- 3.52 kB
- SHA256:
- c84a47f853eb2c6d8e5bba60ccfb8c5ba0503d3c99a54616f579bdb6bb2c17d9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.