Instructions to use debisoft/openmath-mistral-7b-thinking-function_calling-logic-capturing-V0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use debisoft/openmath-mistral-7b-thinking-function_calling-logic-capturing-V0 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("debisoft/openmath-mistral-7b-thinking-function_calling-logic-capturing-V0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d99a8db7ceefbdf199acd0a2407a104d999b3448170572bca77724dd33fc2752
- Size of remote file:
- 5.75 kB
- SHA256:
- ebb577e0370d3c8df88889e3c940179eab28a90821b91fba1b6fc53acb2abc53
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.