Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use fsicoli/whisper-medium-pt-cv19-fleurs2-lr-wu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fsicoli/whisper-medium-pt-cv19-fleurs2-lr-wu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="fsicoli/whisper-medium-pt-cv19-fleurs2-lr-wu")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("fsicoli/whisper-medium-pt-cv19-fleurs2-lr-wu") model = AutoModelForSpeechSeq2Seq.from_pretrained("fsicoli/whisper-medium-pt-cv19-fleurs2-lr-wu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 11.441647597254004, | |
| "total_flos": 4.081970563920691e+20, | |
| "train_loss": 0.03853472162485123, | |
| "train_runtime": 185796.3327, | |
| "train_samples": 34956, | |
| "train_samples_per_second": 2.153, | |
| "train_steps_per_second": 0.135 | |
| } |