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:
# pip install -U transformers accelerate # Load model directly from transformers import HybridFourierLM model = HybridFourierLM.from_pretrained("CodeIsAbstract/HybridTimeScaleModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CodeIsAbstract/HybridTimeScaleModel: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/CodeIsAbstract/HybridTimeScaleModel/resolve/23538fa3ded32f2c893f18115916472ea73aa8f2/training_args.bin
- Command line
-
hf download hf://CodeIsAbstract/HybridTimeScaleModel@23538fa3ded32f2c893f18115916472ea73aa8f2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CodeIsAbstract/HybridTimeScaleModel/resolve/23538fa3ded32f2c893f18115916472ea73aa8f2/training_args.bin
5.2 kB
- Xet hash:
- 98b9a498c647ce0afff0ff1a774f7dc2265b20e4d90d51345fedf17b96a564e0
- Size of remote file:
- 5.2 kB
- SHA256:
- ef8c80f5d40636555b8c09ec97785c8964e446b8d757c55eb76e5b7454841939
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.