Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Romanian
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use VladS159/Whisper_medium_ro_VladS_10000_steps_multi-gpu_smaller_lr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VladS159/Whisper_medium_ro_VladS_10000_steps_multi-gpu_smaller_lr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="VladS159/Whisper_medium_ro_VladS_10000_steps_multi-gpu_smaller_lr")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("VladS159/Whisper_medium_ro_VladS_10000_steps_multi-gpu_smaller_lr") model = AutoModelForSpeechSeq2Seq.from_pretrained("VladS159/Whisper_medium_ro_VladS_10000_steps_multi-gpu_smaller_lr") - Notebooks
- Google Colab
- Kaggle
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