How to use optimum-intel-internal-testing/stsb-bert-tiny-openvino with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("optimum-intel-internal-testing/stsb-bert-tiny-openvino") 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]
How to use optimum-intel-internal-testing/stsb-bert-tiny-openvino with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("optimum-intel-internal-testing/stsb-bert-tiny-openvino") model = AutoModel.from_pretrained("optimum-intel-internal-testing/stsb-bert-tiny-openvino", device_map="auto")
https://huggingface.co/optimum-intel-internal-testing/stsb-bert-tiny-openvino/resolve/main/1_Pooling/config.json
hf download hf://optimum-intel-internal-testing/stsb-bert-tiny-openvino/1_Pooling/config.json
curl -L -o config.json https://huggingface.co/optimum-intel-internal-testing/stsb-bert-tiny-openvino/resolve/main/1_Pooling/config.json
