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:
- 8427dcd312686ccfb0b05191c7ce5a8cc5e81fae52f79740a6a88600fcda0f99
- Size of remote file:
- 260 kB
- SHA256:
- 6a05609b28f5d42b7b748f0f07592545c8f1f6885b9ae8fff64baf56e86b2a18
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