Automatic Speech Recognition
Transformers
Safetensors
Hindi
wav2vec2
mozilla-foundation/common_voice_15_0
mms
Generated from Trainer
Eval Results (legacy)
Instructions to use RSK1987/RohitDataScienceSpeechAnalyticsOutput with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RSK1987/RohitDataScienceSpeechAnalyticsOutput with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="RSK1987/RohitDataScienceSpeechAnalyticsOutput")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("RSK1987/RohitDataScienceSpeechAnalyticsOutput") model = AutoModelForCTC.from_pretrained("RSK1987/RohitDataScienceSpeechAnalyticsOutput") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e71222da4dcf907ebf8b5fe12e22affa59b744c816ca1893cd635b86b4b6c8f
- Size of remote file:
- 1.27 GB
- SHA256:
- 2bc6a74b96827779b01c676c1e2b34fcadf5d84f6e67845c2cd271848c0f7e48
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