Instructions to use razent/mdeberta-cos-sim-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use razent/mdeberta-cos-sim-finetuned with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("razent/mdeberta-cos-sim-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from razent/mdeberta-cos-sim-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/razent/mdeberta-cos-sim-finetuned/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://razent/mdeberta-cos-sim-finetuned/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/razent/mdeberta-cos-sim-finetuned/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- f5eb655b13a993fcb92a2a9228237a9abb514c59231af3093a6420e4b3b7c16f
- Size of remote file:
- 1.11 GB
- SHA256:
- b283435fb7bfc758f0b7a66ad7590a3cbefecfc159179110da21d1487274933f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.