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/encoder_model.onnx from onnx-internal-testing/tiny-random-WhisperForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 143 kB
-
https://huggingface.co/onnx-internal-testing/tiny-random-WhisperForConditionalGeneration/resolve/main/onnx/encoder_model.onnx
- Command line
-
hf download hf://onnx-internal-testing/tiny-random-WhisperForConditionalGeneration/onnx/encoder_model.onnx
-
curl -L -o encoder_model.onnx https://huggingface.co/onnx-internal-testing/tiny-random-WhisperForConditionalGeneration/resolve/main/onnx/encoder_model.onnx
143 kB
- Xet hash:
- 5d98dcdc7377ef1854915fdd9104c89f749d6bfa543371d5fad2bbf427467ac6
- Size of remote file:
- 143 kB
- SHA256:
- f3d3c76e85de8d250e1c60cbe5e492e303b265c988ff2a0828d24caabdf61306
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