Instructions to use FinancialSupport/training_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinancialSupport/training_output with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FinancialSupport/training_output", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f06c080c0514ec15909969f9ec29615d6f2978496752cb14bb8821e33b89ce0
- Size of remote file:
- 976 kB
- SHA256:
- 67af8a09de4a37a23265511d219008b5b6d6ac9ffd6b23c82f9b083268177dd3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.