Instructions to use kazma1/simcse-robertaLarge-matching with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kazma1/simcse-robertaLarge-matching with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, RobertaForCL tokenizer = AutoTokenizer.from_pretrained("kazma1/simcse-robertaLarge-matching") model = RobertaForCL.from_pretrained("kazma1/simcse-robertaLarge-matching", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from kazma1/simcse-robertaLarge-matching: direct link, hf CLI and curl.
- Browser
- Download file 752 kB
-
https://huggingface.co/kazma1/simcse-robertaLarge-matching/resolve/main/tokenizer.json
- Command line
-
hf download hf://kazma1/simcse-robertaLarge-matching/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/kazma1/simcse-robertaLarge-matching/resolve/main/tokenizer.json
752 kB
File too large to display, you can check the raw version instead.