Instructions to use blmoistawinde/roformer-sim-ft-small-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blmoistawinde/roformer-sim-ft-small-chinese with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, RoFormerModelWithPooler tokenizer = AutoTokenizer.from_pretrained("blmoistawinde/roformer-sim-ft-small-chinese") model = RoFormerModelWithPooler.from_pretrained("blmoistawinde/roformer-sim-ft-small-chinese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from blmoistawinde/roformer-sim-ft-small-chinese: direct link, hf CLI and curl.
- Browser
- Download file 81.1 MB
-
https://huggingface.co/blmoistawinde/roformer-sim-ft-small-chinese/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://blmoistawinde/roformer-sim-ft-small-chinese/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/blmoistawinde/roformer-sim-ft-small-chinese/resolve/main/pytorch_model.bin
81.1 MB
- Xet hash:
- 98e382db724530fa04a8c4f44690672b5b63b4a0e20ce217d5b4b892ea7487ca
- Size of remote file:
- 81.1 MB
- SHA256:
- 49ec3a1c88c854f5ffcb0e06e58bc962984ba871dcc4eb07e90d720721e6aad3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.