How to use cointegrated/rubert-tiny2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cointegrated/rubert-tiny2") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3]
How to use cointegrated/rubert-tiny2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("cointegrated/rubert-tiny2") model = AutoModelForPreTraining.from_pretrained("cointegrated/rubert-tiny2", device_map="auto")
https://huggingface.co/cointegrated/rubert-tiny2/resolve/5add408f84b97f3328f0a29f69561d8cb974e4fe/special_tokens_map.json
hf download hf://cointegrated/rubert-tiny2@5add408f84b97f3328f0a29f69561d8cb974e4fe/special_tokens_map.json
curl -L -o special_tokens_map.json https://huggingface.co/cointegrated/rubert-tiny2/resolve/5add408f84b97f3328f0a29f69561d8cb974e4fe/special_tokens_map.json
