Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Portuguese
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use M2LabOrg/whisper-small-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M2LabOrg/whisper-small-pt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="M2LabOrg/whisper-small-pt")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("M2LabOrg/whisper-small-pt") model = AutoModelForSpeechSeq2Seq.from_pretrained("M2LabOrg/whisper-small-pt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4939e9203970b5453b7dc3556df8789fc4c8d2c600a4823d918f1c7c415b7859
- Size of remote file:
- 967 MB
- SHA256:
- 38136bad53f99b3128e68097346669643b30677df4dfb343721b3ec20b13a066
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