Instructions to use onnx-internal-testing/tiny-random-WhisperForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use onnx-internal-testing/tiny-random-WhisperForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="onnx-internal-testing/tiny-random-WhisperForConditionalGeneration")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("onnx-internal-testing/tiny-random-WhisperForConditionalGeneration") model = AutoModelForSpeechSeq2Seq.from_pretrained("onnx-internal-testing/tiny-random-WhisperForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/decoder_with_past_model.onnx from onnx-internal-testing/tiny-random-WhisperForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 3.4 MB
-
https://huggingface.co/onnx-internal-testing/tiny-random-WhisperForConditionalGeneration/resolve/main/onnx/decoder_with_past_model.onnx
- Command line
-
hf download hf://onnx-internal-testing/tiny-random-WhisperForConditionalGeneration/onnx/decoder_with_past_model.onnx
-
curl -L -o decoder_with_past_model.onnx https://huggingface.co/onnx-internal-testing/tiny-random-WhisperForConditionalGeneration/resolve/main/onnx/decoder_with_past_model.onnx
3.4 MB
- Xet hash:
- 95c5a51606ffd04a1fdf1da97754c154c6701fb71481c65e691ca1128b451a9c
- Size of remote file:
- 3.4 MB
- SHA256:
- 47c63bdd5bc8875a6129d91f1562db0721ab7ef8a965d27a2c7da7f87dfaf0db
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