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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21c4286da608bcb1257480bb4a5de0a4ebd5e7669d84f96215a902ba4a24eab8
- Size of remote file:
- 3.52 kB
- SHA256:
- 9a3526b3617e89dc456f2e1199984a3a0615a9ba11f159ab54b636f8929f77f3
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