Instructions to use RUCAIBox/mass-middle-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RUCAIBox/mass-middle-uncased with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RUCAIBox/mass-middle-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from RUCAIBox/mass-middle-uncased: direct link, hf CLI and curl.
- Browser
- Download file 417 MB
-
https://huggingface.co/RUCAIBox/mass-middle-uncased/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://RUCAIBox/mass-middle-uncased/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/RUCAIBox/mass-middle-uncased/resolve/main/pytorch_model.bin
417 MB
- Xet hash:
- 6b485fba085f39cc5db0d8c9c2d7dab376eeec17533a4610c9811f272fe046b5
- Size of remote file:
- 417 MB
- SHA256:
- 827003857128d9ce631dedc5e1f2bc6a7ffbea4bb46e309510e16085a81e71ae
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.