Instructions to use AlanRobotics/rubert-siamese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlanRobotics/rubert-siamese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AlanRobotics/rubert-siamese", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AlanRobotics/rubert-siamese", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AlanRobotics/rubert-siamese: direct link, hf CLI and curl.
- Browser
- Download file 47.2 MB
-
https://huggingface.co/AlanRobotics/rubert-siamese/resolve/d121e4594fc3a8edf3d74ca9b323c4ae42b6c7ab/pytorch_model.bin
- Command line
-
hf download hf://AlanRobotics/rubert-siamese@d121e4594fc3a8edf3d74ca9b323c4ae42b6c7ab/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AlanRobotics/rubert-siamese/resolve/d121e4594fc3a8edf3d74ca9b323c4ae42b6c7ab/pytorch_model.bin
47.2 MB
- Xet hash:
- 1c009e292db26cfc1724bdeb04855d34063bb630b9055fba9bc40eea5d19a2b7
- Size of remote file:
- 47.2 MB
- SHA256:
- 1361d080a1b13c3b6ad04c5b554a3b38cc736d77e1fe5d90f09970e20b21ed76
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.