Automatic Speech Recognition
Transformers
Safetensors
whisper
speech-recognition
multilingual
hindi
bengali
marathi
tamil
telugu
english
distil-whisper
indian-languages
Eval Results (legacy)
Instructions to use TheKingMonarch/whisper-multilang-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheKingMonarch/whisper-multilang-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TheKingMonarch/whisper-multilang-finetuned")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TheKingMonarch/whisper-multilang-finetuned", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
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@@ -79,8 +79,8 @@ from transformers import WhisperProcessor, WhisperForConditionalGeneration
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import librosa
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# Load model and processor
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processor = WhisperProcessor.from_pretrained("
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model = WhisperForConditionalGeneration.from_pretrained("
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# Fix generation config
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model.generation_config.forced_decoder_ids = None
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@@ -149,6 +149,6 @@ If you use this model, please cite:
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title = {{Whisper Multilingual Fine-tuned Model}},
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year = {{2025}},
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publisher = {{Hugging Face}},
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url = {{https://huggingface.co/
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}}
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```
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import librosa
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# Load model and processor
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processor = WhisperProcessor.from_pretrained("TheKingMonarch/whisper-multilang-finetuned")
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model = WhisperForConditionalGeneration.from_pretrained("TheKingMonarch/whisper-multilang-finetuned")
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# Fix generation config
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model.generation_config.forced_decoder_ids = None
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title = {{Whisper Multilingual Fine-tuned Model}},
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year = {{2025}},
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publisher = {{Hugging Face}},
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url = {{https://huggingface.co/TheKingMonarch/whisper-multilang-finetuned}}
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}}
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```
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