Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Spanish
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use M2LabOrg/whisper-small-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M2LabOrg/whisper-small-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="M2LabOrg/whisper-small-es")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("M2LabOrg/whisper-small-es") model = AutoModelForSpeechSeq2Seq.from_pretrained("M2LabOrg/whisper-small-es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c91c2f51c91b27841399e6a24b93f437f800b3991c56e0875322a74a4a07e41a
- Size of remote file:
- 5.24 kB
- SHA256:
- 3c615ff384c748a894bbd4093925fc2449ad18830da50f3550685dbcf3940e6d
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