Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use thabel/whisper-medium-yo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thabel/whisper-medium-yo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="thabel/whisper-medium-yo")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("thabel/whisper-medium-yo") model = AutoModelForSpeechSeq2Seq.from_pretrained("thabel/whisper-medium-yo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from thabel/whisper-medium-yo: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/thabel/whisper-medium-yo/resolve/main/training_args.bin
- Command line
-
hf download hf://thabel/whisper-medium-yo/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/thabel/whisper-medium-yo/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 96e360802355db4ba26b5d34bc9c46da1bb16e9a78a1fa233ea5d144e4ae9b31
- Size of remote file:
- 5.43 kB
- SHA256:
- 20b9f70126e293cedc976e109bf08bb34a61803700d6f3a7f564bd1a31c73e3d
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