Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use juancopi81/whisper-medium-es-train-valid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use juancopi81/whisper-medium-es-train-valid with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="juancopi81/whisper-medium-es-train-valid")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("juancopi81/whisper-medium-es-train-valid") model = AutoModelForSpeechSeq2Seq.from_pretrained("juancopi81/whisper-medium-es-train-valid") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5da412816d759fb68788495e85c742514e9a9a46f7e2394ef576fb7c8f6cbee
- Size of remote file:
- 3.06 GB
- SHA256:
- 7d9e23625b03ebfeefc79a894a75520ddde37b79535322864db1c97923318ddd
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