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:
- a797a4b0831a1270ca0364123958b2fb355ce320715cfe993b42c5379d2a75ed
- Size of remote file:
- 40.9 MB
- SHA256:
- f28387c92ade2f963767b017f147e3c645d2601176e2dd95b5393033b241019c
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