Instructions to use CodeIsAbstract/HybridTimeScaleModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeIsAbstract/HybridTimeScaleModel with Transformers:
# Load model directly from transformers import HybridFourierLM model = HybridFourierLM.from_pretrained("CodeIsAbstract/HybridTimeScaleModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from CodeIsAbstract/HybridTimeScaleModel: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/CodeIsAbstract/HybridTimeScaleModel/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://CodeIsAbstract/HybridTimeScaleModel/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CodeIsAbstract/HybridTimeScaleModel/resolve/main/last-checkpoint/training_args.bin
5.2 kB
- Xet hash:
- af1ab8305ce08694622aadcab05845e2f42f6116506ca81c935c9768493f6cbd
- Size of remote file:
- 5.2 kB
- SHA256:
- de39541c4d3c2c8cd3db89cc5a7ea96a1526b7e8be52cafa957494d7daabed0f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.