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_q4.onnx from onnx-internal-testing/tiny-random-WhisperForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 3.39 MB
-
https://huggingface.co/onnx-internal-testing/tiny-random-WhisperForConditionalGeneration/resolve/main/onnx/decoder_with_past_model_q4.onnx
- Command line
-
hf download hf://onnx-internal-testing/tiny-random-WhisperForConditionalGeneration/onnx/decoder_with_past_model_q4.onnx
-
curl -L -o decoder_with_past_model_q4.onnx https://huggingface.co/onnx-internal-testing/tiny-random-WhisperForConditionalGeneration/resolve/main/onnx/decoder_with_past_model_q4.onnx
3.39 MB
- Xet hash:
- 42c896d919b2ccec9d985e752f4352697918c147c31c362c5f64d15d601e6bbc
- Size of remote file:
- 3.39 MB
- SHA256:
- 8163c454ddedb0674e465099e2645ba61c873305a0a6f98bec5b6f53c2a5a123
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