Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Spanish
whisper
Generated from Trainer
Instructions to use igarciahuidobro/whisper-tiny-300-audios with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use igarciahuidobro/whisper-tiny-300-audios with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="igarciahuidobro/whisper-tiny-300-audios")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("igarciahuidobro/whisper-tiny-300-audios") model = AutoModelForSpeechSeq2Seq.from_pretrained("igarciahuidobro/whisper-tiny-300-audios") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
README.md
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library_name: transformers
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license: apache-2.0
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base_model: rasel35/whisper-base-es-medical-terms
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tags:
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metrics:
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model-index:
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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#
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This model is a fine-tuned version of [rasel35/whisper-base-es-medical-terms](https://huggingface.co/rasel35/whisper-base-es-medical-terms) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.4543
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- Wer: 19.9630
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library_name: transformers
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- spa
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license: apache-2.0
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base_model: rasel35/whisper-base-es-medical-terms
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tags:
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metrics:
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model-index:
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- name: Whisper Pre Tuned 300 Audios - Nacho v2.0
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Whisper Pre Tuned 300 Audios - Nacho v2.0
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This model is a fine-tuned version of [rasel35/whisper-base-es-medical-terms](https://huggingface.co/rasel35/whisper-base-es-medical-terms) on the 300 audios 1.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4543
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- Wer: 19.9630
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