Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use LeonM78Code/whisper-medium-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LeonM78Code/whisper-medium-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="LeonM78Code/whisper-medium-dv")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("LeonM78Code/whisper-medium-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("LeonM78Code/whisper-medium-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from LeonM78Code/whisper-medium-dv: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/LeonM78Code/whisper-medium-dv/resolve/main/training_args.bin
- Command line
-
hf download hf://LeonM78Code/whisper-medium-dv/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/LeonM78Code/whisper-medium-dv/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 6c7eb69a89c2d3eed5f2df896dd84570a06d128ec95d813262ef6c5684465b8b
- Size of remote file:
- 5.5 kB
- SHA256:
- 055c2040a1971ef0b021030b8113bc40115fc6f263298490aaf6b25eae8d5097
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