Automatic Speech Recognition
Transformers
PyTorch
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use steja/whisper-small-occitan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use steja/whisper-small-occitan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="steja/whisper-small-occitan")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("steja/whisper-small-occitan") model = AutoModelForSpeechSeq2Seq.from_pretrained("steja/whisper-small-occitan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#2
by librarian-bot - opened
README.md
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@@ -7,21 +7,22 @@ datasets:
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- google/fleurs
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metrics:
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- wer
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model-index:
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- name: Whisper_small_Occitan
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: google/fleurs
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type: google/fleurs
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config: oc_fr
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split: test
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metrics:
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type: wer
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value: 39.84848484848485
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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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- google/fleurs
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metrics:
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- wer
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base_model: bofenghuang/whisper-small-cv11-french
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model-index:
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- name: Whisper_small_Occitan
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results:
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- task:
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type: automatic-speech-recognition
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name: Automatic Speech Recognition
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dataset:
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name: google/fleurs
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type: google/fleurs
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config: oc_fr
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split: test
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metrics:
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- type: wer
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value: 39.84848484848485
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name: Wer
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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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