Instructions to use debisoft/Qwen2-Audio-7B-Instruct-thinking-function_calling-quant-V0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use debisoft/Qwen2-Audio-7B-Instruct-thinking-function_calling-quant-V0 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("debisoft/Qwen2-Audio-7B-Instruct-thinking-function_calling-quant-V0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3874e391e1803ce6fb8308689eb97d495edeb91482daa672a6f045ec9f5957a3
- Size of remote file:
- 5.69 kB
- SHA256:
- f868c2118936b54b5da3ccf816f7f52262616d164815a10fa2ffbca5342fca91
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.