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
File size: 130 Bytes
ef716c4 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:929ece591703c9213a3a547d42598486f6a26d07cb1579c553c50e6020df75e9
size 79725
|