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:
- d1b7c8dac25644529d7e0e5dfac8ce4becd2445c695c8dc88d6b4288a694adf9
- Size of remote file:
- 12 MB
- SHA256:
- 77c80400675925fa52dce7aa9646fbd169fec619ee46dcaf41b3782b524283c2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.