Sentence Similarity
sentence-transformers
Safetensors
Transformers
roberta
feature-extraction
text-embeddings-inference
Instructions to use shangrilar/klue-roberta-base-klue-sts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use shangrilar/klue-roberta-base-klue-sts with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("shangrilar/klue-roberta-base-klue-sts") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use shangrilar/klue-roberta-base-klue-sts with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("shangrilar/klue-roberta-base-klue-sts") model = AutoModel.from_pretrained("shangrilar/klue-roberta-base-klue-sts", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config_sentence_transformers.json from shangrilar/klue-roberta-base-klue-sts: direct link, hf CLI and curl.
- Browser
- Download file 123 Bytes
-
https://huggingface.co/shangrilar/klue-roberta-base-klue-sts/resolve/7198ee8bcb0a1028d0d8cb4e645fdccafdfa0d5c/config_sentence_transformers.json
- Command line
-
hf download hf://shangrilar/klue-roberta-base-klue-sts@7198ee8bcb0a1028d0d8cb4e645fdccafdfa0d5c/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/shangrilar/klue-roberta-base-klue-sts/resolve/7198ee8bcb0a1028d0d8cb4e645fdccafdfa0d5c/config_sentence_transformers.json
123 Bytes
| { | |
| "__version__": { | |
| "sentence_transformers": "2.2.2", | |
| "transformers": "4.35.2", | |
| "pytorch": "2.1.0+cu121" | |
| } | |
| } |