Instructions to use hf-internal-testing/tiny-random-Qwen2_5OmniForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Qwen2_5OmniForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="hf-internal-testing/tiny-random-Qwen2_5OmniForConditionalGeneration")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Qwen2_5OmniForConditionalGeneration") model = AutoModelForTextToWaveform.from_pretrained("hf-internal-testing/tiny-random-Qwen2_5OmniForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f59fce72f616172554e519584834dd7b49bdc28f94a018b533f17d49de8d78d1
- Size of remote file:
- 11.4 MB
- SHA256:
- 8441917e39ae0244e06d704b95b3124795cec478e297f9afac39ba670d7e9d99
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