Instructions to use voidism/diffcse-roberta-base-trans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidism/diffcse-roberta-base-trans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="voidism/diffcse-roberta-base-trans")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("voidism/diffcse-roberta-base-trans") model = AutoModel.from_pretrained("voidism/diffcse-roberta-base-trans") - Notebooks
- Google Colab
- Kaggle
add models to NAACL 2022 organization
Hi, thanks for adding the model to huggingface for diffcse, we are having a event on Hugging Face for NAACL 2022 to submit models/datasets and web demos for a chance to win prizes, it would be great if you can join, see more info here: https://huggingface.co/NAACL2022 and the link to join the organization here: https://huggingface.co/organizations/NAACL2022/share/FnuCfwNhiIRWAlngiEkLcwuUrMDMTCPbje
for adding the existing models you can simply clone and push them to the NAACL 2022 organization similar to github
@voidism just reaching out to see if there is an update on this also a gradio demo can be setup with a few lines of code using the inference api integration with Hugging Face, see: https://gradio.app/docs/#load-header