Instructions to use tuhailong/SimCSE-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tuhailong/SimCSE-bert-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tuhailong/SimCSE-bert-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from tuhailong/SimCSE-bert-base: direct link, hf CLI and curl.
- Browser
- Download file 818 MB
-
https://huggingface.co/tuhailong/SimCSE-bert-base/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://tuhailong/SimCSE-bert-base@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/tuhailong/SimCSE-bert-base/resolve/refs%2Fpr%2F1/optimizer.pt
818 MB
- Xet hash:
- 54a8b2052adbf4b6adc9d4fbf53ba3997f8d19e17682250bea492247bb41cec8
- Size of remote file:
- 818 MB
- SHA256:
- c21ea3ae41b7a307c3e43373e01317e591bbc9fc2ea6e0232202a704d5435e9a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.