Instructions to use kppkkp/OneChart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kppkkp/OneChart with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="kppkkp/OneChart", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kppkkp/OneChart", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 676a499573d41ca4a024c3139cad4a68b88d537a699b7d58cb6af4017bbbd764
- Size of remote file:
- 525 MB
- SHA256:
- 15ab0e9971384db1f17414d6b1e4d9d55bfcdb80d810dfb161b316fb10b6220b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.