Instructions to use leoschneider/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leoschneider/results with Transformers:
# Load model directly from transformers import AutoTokenizer, TimeSeriesTransformerForPrediction tokenizer = AutoTokenizer.from_pretrained("leoschneider/results") model = TimeSeriesTransformerForPrediction.from_pretrained("leoschneider/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a90f1fd9db2ca747334a3c38200c1182ada737f5d288ce9401b269f4d63dc90d
- Size of remote file:
- 4.16 kB
- SHA256:
- 47bcea3c4d1191b7f7510c53c96997b39d2fe421c3f6bc2267dc217f35411d5b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.