Instructions to use hf-tiny-model-private/tiny-random-WhisperForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-WhisperForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-tiny-model-private/tiny-random-WhisperForConditionalGeneration")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-WhisperForConditionalGeneration") model = AutoModelForSpeechSeq2Seq.from_pretrained("hf-tiny-model-private/tiny-random-WhisperForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
File size: 181 Bytes
cc7425a | 1 2 3 4 5 6 7 8 9 | {
"_from_model_config": true,
"bos_token_id": 50257,
"decoder_start_token_id": 85,
"eos_token_id": 50257,
"pad_token_id": 50257,
"transformers_version": "4.28.0.dev0"
}
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