Audio-Text-to-Text
Transformers
Safetensors
qwen2_5_omni
text-to-audio
audio
audio-question-answering
audio-classification
candidate-scoring
Instructions to use shlv/AudioJev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shlv/AudioJev with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("shlv/AudioJev") model = AutoModelForMultimodalLM.from_pretrained("shlv/AudioJev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model-00003-of-00005.safetensors from shlv/AudioJev: direct link, hf CLI and curl.
- Browser
- Download file 3.92 GB
-
https://huggingface.co/shlv/AudioJev/resolve/d506a7b75abbf13f2cd4a0866165b39093e75775/model-00003-of-00005.safetensors
- Command line
-
hf download hf://shlv/AudioJev@d506a7b75abbf13f2cd4a0866165b39093e75775/model-00003-of-00005.safetensors
-
curl -L -o model-00003-of-00005.safetensors https://huggingface.co/shlv/AudioJev/resolve/d506a7b75abbf13f2cd4a0866165b39093e75775/model-00003-of-00005.safetensors
3.92 GB
- Xet hash:
- e4aad3ea0c9deb8f606047a572421903c6c71b9a9d59ea71c54128d84df37345
- Size of remote file:
- 3.92 GB
- SHA256:
- 35b3a36a2d092b19a0427c016c8d28cea4a4e0b5f3dcf59934b7d74eded521af
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