Instructions to use Yiming1234/4k-steps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yiming1234/4k-steps with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Yiming1234/4k-steps", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2000/optimizer.bin from Yiming1234/4k-steps: direct link, hf CLI and curl.
- Browser
- Download file 63.8 GB
-
https://huggingface.co/Yiming1234/4k-steps/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://Yiming1234/4k-steps/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Yiming1234/4k-steps/resolve/main/checkpoint-2000/optimizer.bin
63.8 GB
- Xet hash:
- defc408261da5f4770749ef70d082029be80276a06298b401e99352cc6a37aec
- Size of remote file:
- 63.8 GB
- SHA256:
- c3ad5350781a39b7bfba4d1ed3fe318cddb01cd2b280641bc8e35f407e6cae3e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.