Instructions to use paulo037/StableCode-DPO2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paulo037/StableCode-DPO2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("paulo037/StableCode-DPO2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-150/optimizer.pt from paulo037/StableCode-DPO2: direct link, hf CLI and curl.
- Browser
- Download file 204 MB
-
https://huggingface.co/paulo037/StableCode-DPO2/resolve/2648e0ee17acea1d5fa560dc46bb4b97825db803/checkpoint-150/optimizer.pt
- Command line
-
hf download hf://paulo037/StableCode-DPO2@2648e0ee17acea1d5fa560dc46bb4b97825db803/checkpoint-150/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/paulo037/StableCode-DPO2/resolve/2648e0ee17acea1d5fa560dc46bb4b97825db803/checkpoint-150/optimizer.pt
204 MB
- Xet hash:
- 39d983f887b4b9eb418dafa118c361f76db4acf03b49cde61a503ee9433abf87
- Size of remote file:
- 204 MB
- SHA256:
- 5ab71474f1340a11854e3319b954ea351c8be2510804a1eaf6dd07b3b1867c98
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.