Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Portuguese
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use M2LabOrg/whisper-medium-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M2LabOrg/whisper-medium-pt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="M2LabOrg/whisper-medium-pt")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("M2LabOrg/whisper-medium-pt") model = AutoModelForSpeechSeq2Seq.from_pretrained("M2LabOrg/whisper-medium-pt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5404754fa7f22f49c35e2ca35fe487024cbd9f1a113f0f92db5fa10cb095c652
- Size of remote file:
- 3.06 GB
- SHA256:
- a57081a25855524e4a6b39dfa5d64459f06ba5cd11dd7f96e838d4dc063286a9
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