Instructions to use optimum-internal-testing/tiny-random-whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use optimum-internal-testing/tiny-random-whisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="optimum-internal-testing/tiny-random-whisper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("optimum-internal-testing/tiny-random-whisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("optimum-internal-testing/tiny-random-whisper") - Notebooks
- Google Colab
- Kaggle
Upload WhisperForConditionalGeneration
Browse files- generation_config.json +0 -10
- model.safetensors +1 -1
generation_config.json
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"bos_token_id": 50257,
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"eos_token_id": 50257,
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"is_multilingual": true,
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"lang_to_id": {
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"<|af|>": 50327,
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"bos_token_id": 50257,
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"decoder_start_token_id": 50258,
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"eos_token_id": 50257,
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"is_multilingual": true,
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"lang_to_id": {
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"<|af|>": 50327,
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model.safetensors
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size 871760
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size 871760
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