Instructions to use dsfsi/simcse-dna with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dsfsi/simcse-dna with Transformers:
# Load model directly from transformers import AutoTokenizer, BertForCL tokenizer = AutoTokenizer.from_pretrained("dsfsi/simcse-dna") model = BertForCL.from_pretrained("dsfsi/simcse-dna", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dsfsi/simcse-dna: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/dsfsi/simcse-dna/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dsfsi/simcse-dna/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dsfsi/simcse-dna/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- 356055e031542863f61d54ef5c8868329e0cfd2d92c487f054ceb23bc1b67299
- Size of remote file:
- 440 MB
- SHA256:
- e36cc3ca19e3cd19c0fa0dca4c4c451fd7e038d95c0fce737c739bb46768307c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.