Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Greek
whisper
hf-asr-leaderboard
whisper-medium
mozilla-foundation/common_voice_11_0
greek
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use emilios/whisper-medium-el with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emilios/whisper-medium-el with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="emilios/whisper-medium-el")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("emilios/whisper-medium-el") model = AutoModelForSpeechSeq2Seq.from_pretrained("emilios/whisper-medium-el", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from emilios/whisper-medium-el: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/emilios/whisper-medium-el/resolve/main/training_args.bin
- Command line
-
hf download hf://emilios/whisper-medium-el/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/emilios/whisper-medium-el/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- b5ba27f21351c4078ce4384b12b786227a6c2e8521c644b218edb255f941f16f
- Size of remote file:
- 3.64 kB
- SHA256:
- 100e73adb4d90efbc7017afb41284e00283fb993eaadf9183f82ac4273f0da38
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.